assured communications in challenging and contested...

Defence Research andDevelopment Canada

Recherche et developpementpour la defense Canada

Assured communications in challenging and contested

environments

Final Report

T.J. Willink

DRDC – Ottawa Research Centre

Defence Research and Development Canada

Scientific ReportDRDC-RDDC-2016-R107June 2016

Assured communications in challenging andcontested environmentsFinal Report

T.J. Willink


Defence Research and Development CanadaScientific Report

DRDC-RDDC-2016-R107

June 2016

c© Her Majesty the Queen in Right of Canada, as represented by the Minister of NationalDefence, 2016

c© Sa Majesté la Reine (en droit du Canada), telle que réprésentée par le ministre de laDéfense nationale, 2016

Abstract

The Assured Communications in Challenging and Contested Environments (AC3E)Project comprised demonstrations of techniques for robust and reliable communicationsin remote and/or under-serviced regions such as the Arctic, and the developmentof concepts and techniques for flexible and adaptive spectrum access to providerobust networked communications in dynamic environments. Policy-based decisionmaking combining situational awareness and user requirements was the foundation fordemonstrations of the Northern Access Node and real-time spectrum access testbeds,which showed how robust channel access can be achieved with low overhead andoperator burden.

As modern waveforms are quite interference tolerant, conventional spectrum manage-ment approaches are unnecessarily rigorous and require expertise and effort. Advancesin an autonomous, interference-tolerant concept have been made, based on a gracefulfrequency adaptation strategy. This has been found to be an efficient and robustbasis for dynamic spectrum access in mobile radio networks. Spatio-temporal channelmeasurements and analyses were undertaken to support the investigations and toprovide more realistic evaluations of adaptive capabilities and requirements.

To respond to increasing demands on the limited available spectrum for militarycommunications, it will be necessary to incorporate new strategies for spectrum accessinto the current spectrum regulatory, policy and management regime. The advancesmade within this Project show that both lightly-managed policy-based systems andautonomous spectrum access are worthwhile strategies for modernising spectrumaccess. Both these approaches use local spectrum situational awareness observations:it was shown that using a small number of simple, remote sensors to generate aspectrum occupancy map is not sufficiently reliable to support real-time spectrummanagement.

Significance for defence and security

Robust and resilient communication capabilities are required to enable commander andstaff to distribute and share, control and manage, and protect information. This is aparticular challenge in Arctic regions, where radio propagation conditions and limitedpower restrict throughput and range, and in urban environments, where interference,mobility and interference degrade link quality. In coalition operations, spectrum canbecome particularly congested and intentional and accidental interference reduces thecapacity of links to support communications.

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The AC3E Project has developed and demonstrated techniques to support robustand resilient communications in Arctic and remote regions, using a policy-basedarchitecture that combines situational awareness and user quality of service andprotection requirements to select appropriate bearers. An extension of this capabilityprovides a lightly managed approach to spectrum access, matching frequency selectionto user needs.

To address the increasing demand on spectrum resources, concepts and techniques forflexible and dynamic access to spectrum have been investigated and validated. Theseautonomous dynamic spectrum access strategies enable users to make the best use oflocal spectrum opportunities, increasing overall efficiency and throughput. Robustnessand resilience are achieved by exploiting modern waveforms’ interference tolerance,and low overhead reduces security vulnerabilities.

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Résumé

Le projet Communications assurées dans des environnements difficiles et contestés(AC3E) a permis la démonstration de techniques pour assurer des communicationssolides et fiables dans des régions éloignées et mal desservies comme l’Arctique, demême que l’élaboration de concepts et de techniques en vue d’un accès souple etadaptatif au spectre pour des communications en réseau soutenues dans un environne-ment dynamique. À l’aide d’une prise de décision fondée sur les politiques mariantconnaissance de la situation et besoins des utilisateurs, l’équipe a pu démontrer lesbancs d’essai du nœud d’accès au Nord et au spectre en temps réel, et ainsi montrercomment obtenir un accès stable et à peu de frais au canal sans surcharger l’utilisateur.

Comme les formes d’ondes modernes sont peu sensibles aux interférences, les méthodestraditionnelles de gestion du spectre sont inutilement rigoureuses et nécessitent uneexpertise et un certain effort. Or, on a perfectionné un concept autonome et insensibleaux interférences fondé sur une stratégie raffinée d’adaptation fréquentielle. Ce concepts’est avéré une base solide et efficace en permettant un accès dynamique au spectredes réseaux radio mobiles. Des mesures et analyses spatiotemporelles des canaux ontappuyé les études et permis d’évaluer les besoins et les capacités d’adaptation de façonplus réaliste.

Pour satisfaire la demande croissante de communications militaires dans les limites duspectre, il faudra intégrer de nouvelles stratégies d’accès au régime de réglementation,de politique et de gestion du spectre actuel. Les progrès réalisés dans le cadre de ceprojet ont prouvé l’utilité des systèmes à gestion peu serrée fondés sur les politiqueset celle de l’accès autonome afin de le moderniser. Ces deux méthodes sont fondéessur des observations de connaissance de la situation visant le spectre : l’utilisation dequelques télécapteurs simples ne permet pas de produire une carte d’occupation duspectre suffisamment fiable pour faciliter la gestion du spectre en temps réel.

Importance pour la défense et la sécurité

Une communicabilité à la fois solide et souple est nécessaire au commandementcomme au personnel pour distribuer et partager, contrôler et gérer, ainsi que protégerl’information. Cela se révèle particulièrement ardu dans les régions arctiques, oùles conditions de propagation des ondes radio et l’alimentation électrique limitéeréduisent le débit et la portée des communications, de même qu’en milieu urbain oùles interférences et la mobilité en réduisent la qualité. Les opérations coalisées risquentd’encombrer sérieusement le spectre et les interférences produites délibérément ouaccidentellement réduisent la capacité des liens de communications.

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Le projet AC3E a permis l’élaboration et la démonstration de techniques qui assurentdes communications solides et souples dans l’Arctique et les régions éloignées à l’aided’une architecture fondée sur les politiques et combinant la connaissance de la situation,la qualité du service aux utilisateurs et le respect des exigences en matière de protectionpour déterminer le lien approprié. Une extension de cette capacité permet une gestionpeu serrée de l’accès au spectre afin de choisir les fréquences en fonction des besoinsdes utilisateurs.

Pour satisfaire la demande croissante en matière de ressources spectrales, on a étudiéet validé des concepts et des techniques permettant un accès souple et dynamiqueau spectre. Ces stratégies en vue d’un accès autonome et dynamique permettent uneutilisation optimale des possibilités du spectre et accroissent le débit et l’efficacité del’ensemble des communications. Exploiter l’insensibilité des formes d’ondes modernesaux interférences permet des communications solides et fiables à peu de frais et réduitles vulnérabilités en matière de sécurité.

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Table of contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Significance for defence and security . . . . . . . . . . . . . . . . . . . . . . . i

Résumé . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Importance pour la défense et la sécurité . . . . . . . . . . . . . . . . . . . . . iii

Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

List of figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Arctic communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

3 Spectrum access . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.1 Policy-based spectrum access . . . . . . . . . . . . . . . . . . . . . . 8

3.2 Spectrum sharing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.2.1 Spectrum overloading . . . . . . . . . . . . . . . . . . . . . . 13

3.2.2 Frequency adaptation . . . . . . . . . . . . . . . . . . . . . 14

3.2.3 Altruism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3.2.4 Spectrum labelling . . . . . . . . . . . . . . . . . . . . . . . 24

3.2.5 MAC protocols . . . . . . . . . . . . . . . . . . . . . . . . . 26

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3.2.6 Interference alignment . . . . . . . . . . . . . . . . . . . . . 27

3.3 Shared spectrum situational awareness . . . . . . . . . . . . . . . . . 29

3.4 Spectral efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3.4.1 Multi-frequency measurements . . . . . . . . . . . . . . . . . 33

3.4.2 Multi-node measurements . . . . . . . . . . . . . . . . . . . 35

3.4.3 Air-to-ground measurements . . . . . . . . . . . . . . . . . . 38

4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Abbreviations and acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

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List of figures

Figure 1: Northern network architecture . . . . . . . . . . . . . . . . . . . . 4

Figure 2: Northern access node policy system architecture . . . . . . . . . . 5

Figure 3: Northern access node field demonstration . . . . . . . . . . . . . . 6

Figure 4: Emulated dynamic spectrum access system . . . . . . . . . . . . . 9

Figure 5: Policy engine components . . . . . . . . . . . . . . . . . . . . . . 10

Figure 6: Frequency domain representation of overloading spectrum . . . . . 13

Figure 7: Multiple user pair scenario . . . . . . . . . . . . . . . . . . . . . . 16

Figure 8: Trade-offs between user reliability and spectrum resource usage . . 17

Figure 9: Characteristics of dynamic system . . . . . . . . . . . . . . . . . . 18

Figure 10: Robustness of dynamic system . . . . . . . . . . . . . . . . . . . . 19

Figure 11: Resilience of dynamic system . . . . . . . . . . . . . . . . . . . . . 20

Figure 12: Frequency updates after disruptive event . . . . . . . . . . . . . . 21

Figure 13: Network coordination framework . . . . . . . . . . . . . . . . . . . 22

Figure 14: Cross-layer protocol architecture . . . . . . . . . . . . . . . . . . . 23

Figure 15: Spectrum label embedded in host signal . . . . . . . . . . . . . . . 25

Figure 16: Received host and label constellations . . . . . . . . . . . . . . . . 26

Figure 17: Interference alignment . . . . . . . . . . . . . . . . . . . . . . . . 27

Figure 18: Terrain map, West Carleton area . . . . . . . . . . . . . . . . . . 30

Figure 19: Spectrum occupancy characteristics . . . . . . . . . . . . . . . . . 30

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Figure 20: Belief-based spectral occupancies . . . . . . . . . . . . . . . . . . 32

Figure 21: CRC MIMO channel sounder . . . . . . . . . . . . . . . . . . . . . 34

Figure 22: Map of multi-node measurement locations . . . . . . . . . . . . . 36

Figure 23: Measured diversity characteristics . . . . . . . . . . . . . . . . . . 37

Figure 24: AFRL UAV with CRC mini-sounder in cargo hold . . . . . . . . . 38

Figure 25: Plane and spherical waves at ground array . . . . . . . . . . . . . 39

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Acknowledgements

Many thanks to the project team for their dedication and innovative contributions tothis research program: Geoff Colman, Kareem Baddour, Chris Squires, HumphreyRutagemwa, Sarah Dumoulin and Francis St. Onge.

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1 Introduction

Accurate and timely situational awareness (SA) and effective command and control(C2) need reliable information exchange, which is particularly difficult to provide inphysically challenging environments, such as urban areas, where multipath and mobilitydegrade link quality, or Arctic regions, where radio propagation conditions and limitedpower restrict throughput and range. Additional challenges are experienced in thespectrally congested conditions that occur in coalition operations, where intentionaland accidental interference reduce the capacity of links to support communications.

The Assured Communications in Challenging and Contested Environments (AC3E)Project was formulated to demonstrate previously-proposed concepts for robust andreliable communications in remote and/or underserviced regions such as the Arctic or indisaster recovery operations, and to develop concepts, techniques and demonstrationsfor flexible and adaptive access to spectrum in dynamic and congested environments.This is the final report for the AC3E Project, providing an overview of the technicalcontributions and achievements. An extensive list of project outputs, in the form ofjournal and conference papers as well as technical reports and memoranda, is providedas the source of more detailed information.

1.1 Scope

The elements of the AC3E Project reported here are Arctic communications andspectrum access. In addition, the Project Charter [2] included a scoping study onS&T required to support developments in federated networks, which is reportedelsewhere [3]. A fourth element, the fugitive signal interceptor, was incorporated intothe Project Charter for administrative purposes, was led and reported separately.

The Arctic Communications element of the AC3E Project was the completion ofa former applied research project (ARP), ‘Northern Communications’, which haddeveloped the concept of a Northern Access Node (NAN) as a ground entry stationproviding links over a variety of long-range bearers such as HF, troposcatter and satcom.These suffer from different challenges and costs, affecting reliability, bandwidth andvulnerability. The preceding project had implemented an automated control algorithmbased on quality of protection (QoP) principles, enabling agile and flexible use ofcommunications resources to support requirements for confidentiality, integrity andavailability through bearer selection. Within the AC3E Project, the focus was on thedemonstration of a NAN testbed and the integration of mission-specific links for local,mobile users. The latter capability was achieved in parallel with the policy-basedspectrum access (PBSA) sub-element of the Spectrum Access project element.

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The largest element of the AC3E Project was Spectrum Access, which was thecompletion of a previous ARP, ‘Effective spectrum access in a mobile, networkedenvironment’. The work in both the ARP and the AC3E Project is reported here.The objectives were to increase the efficacy and robustness of spectrum access forjoint operations through adaptivity and interference tolerance, and to enhance thespectral efficiency of networked communications. This work addressed new strategiesfor accessing spectrum, providing more flexibility than the conventional spectrummanagement approach that assigns fixed, specific bandwidths to users. Allowingdynamic assignments or autonomous selection of frequency occupation may facilitateusers to mitigate interference in contested environments, and to take advantage ofspectral vacancies to support high bandwidth applications. Technologies are advancingto exploit potential opportunities opened by new regulations in some spectrum bands,and these will impact future CAF radio operations. However, challenges, costs and risksare associated with each potential approach to modernising spectrum management,and changes to regulation and policy, as well as future procurements, must also takethese into account.

The Spectrum Access element comprised four sub-elements:

• Policy-based spectrum access Lightly-managed dynamic spectrum access can beachieved through the use of clearly defined policies for channel selection. Channelprobing to evaluate link quality is used as an input into the policy-based decisionengine, which directs radios when and how to change channels. This sub-elementand the mission-specific links component of the Arctic Communications elementwere addressed together.

• Spectrum sharing An interference-tolerant approach to spectrum access forsome CAF spectrum users was proposed in earlier work, contrasting with theinterference-avoidance principles used in conventional spectrum management.In this sub-element, strategies and technologies for effective spectrum sharingamong mobile users were developed and evaluated, to support future spectrumregulatory decisions, policy development and technology advancement.

• Shared spectrum situational awareness In this sub-element, techniques for gen-erating a spectrum occupancy map, displaying shared spectrum SA obtainedby combining inputs from many simple spectrum sensors, were evaluated. Sucha map, if sufficiently reliable, might support dynamic spectrum assignmentdecisions made by a central controller with visibility over a large geographicarea and spectrum band.

• Spectral efficiency To support the development and evaluation of spectrallyefficient and effective communications and spectrum access strategies, goodmodels of the radio environment are required. Radio channel measurement

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campaigns, modelling and analysis, and evaluation of signalling strategies wereundertaken in this sub-element.

1.2 Context

The AC3E Project was part of DRDC’s C2/CIS Program within the JFD Portfolio.The Program’s main objective is ‘to support commanders and staff at the strategic,operational and joint mission level of command in their effort to enhance effectivenessby gaining, maintaining and exploiting information and decision advantage’ [2]. Theproject was delivered by the Communications Research Centre (CRC).

The AC3E Project was developed to support the CAF Intermediate Outcome [4]:

The CAF employs improved command and control through an adaptable anddefence information sharing and collaboration environment that achieves:

a. exercise of authority and direction over assigned, allocated andattached forces; and

b. management of force and orchestration of effects and outcomes inresponse to government direction.

Specifically, the AC3E Project addresses this Immediate Outcome [4]:

A Communication Information System that enables commander and staffto distribute and share, control and manage, and protect information.

The JFD Portfolio Program Brief gives the following high level deliverables for theAC3E Project [4]:

1. validated concepts and techniques to support robust and resilientcommunications in Arctic and remote regions; and

2. validated concepts, techniques and policy recommendations for theintegration of advanced spectrum access technologies into operations.


2 Arctic communications

The Northern Communications applied research project (ARP) ran until March 2014,after which remaining deliverables on the Northern Access Node (NAN) componentwere completed within the AC3E Project. These are described in detail in [5].

The northern network architecture proposed in the Northern Communications project,illustrated in Figure 1, provides a mesh-like topology to connect NANs. Each nodehas at least two long range links, such as satcom, HF, troposcatter or fibre, and inmost cases, is connected to a southern operations centre. The nodes also have local‘mission-specific’ links which provide connectivity to mobile nodes within short range.

Figure 1: Northern network architecture [5].

The optimisation of the long range link usage based on application requirementswas undertaken in the Northern Communications project, building on many years ofpolicy-based traffic management (PBTM) work at CRC and on collaborative effortswith NATO and TTCP. The work was completed and demonstrated within the AC3EProject. The previous project included analyses of the bearer capabilities, and theimpact of various scenarios on existing Arctic communications infrastructure [19,20].

The mobile node link capability was developed and demonstrated within the AC3EProject, where it was approached using a dynamic spectrum access focus to alignwith CRC’s S&T directions in spectrum management, regulation and innovation. It isdescribed in Section 3.1.

The NAN testbed comprises commercial network equipment including Cisco routers,Riverbed Steelhead optimisers and network encryption devices. There are also situa-


tional awareness sensors, such as network topology and performance agents.

The core of the NAN is the policy system. It is used to automatically select bearerresources to adapt to changing link availability and user demand. Policies are operatingrules, usually pre-defined, which are used to manage the network with minimaloperator intervention. In the NAN, policies are written to meet user requirementsin the categories confidentiality, integrity and availability. These fall within the‘quality of protection’ (QoP) concept developed within the Policy-Enabled CoalitionCommunications (PECC) project of TTCP C3I Technical Panels 8 (Networks) and 11(Security).

The architecture of the NAN policy server architecture is illustrated in Figure 2.Policies are input at the policy management point, and passed to the policy analysismodule, which implements the decision logic by means of a rule engine, computingQoP scores using static configurations from the repository and dynamic networkinformation. This module determines the best link for the specified application basedon the QoP scores.

When the route is selected, it is sent to the policy enforcers, which reconfigure theCisco routers as required. The situational awareness sensors monitor the networkstatus and when a change is detected, e.g., the loss of a link, the rule engine isre-engaged and a new route is chosen.

Figure 2: Northern access node policy system architecture [5].


This system was demonstrated in the lab in spring 2014, where attendance includedDND and CAF stakeholders. Several applications, including VoIP and real-time video,were shown being routed over different simulated links in response to user-specifiedpreferences for the three QoP parameters: confidentiality, integrity and availability.User preferences were input easily and intuitively using a slider on a graphical userinterface.

In October 2014, a live demonstration of the NAN concept was held, also attendedby DND and CAF personnel. The NAN components were installed in a short rack,Figure 3(a), which was mounted in a trailer in the open area behind CRC, Figure 3(b).This demonstration used live commercial satcom, cellular and WiFi links to connectto a base inside the CRC lab.

(a) NAN prototype (b) NAN demonstration location

Figure 3: Northern access node field demonstration [5].

The live demonstration showed the potential of the NAN to operate not only in anArctic region, but also in a remote or challenging environment, for example, as partof a CAF Disaster Assistance Response Team (DART) deployment to an emergencyzone.

The development and demonstration of mission-specific links was undertaken inconjunction with the Spectrum Access element of the AC3E Project, and is reportedin the next section.


3 Spectrum access

In challenging and contested spectrum environments, providing sufficient channelbandwidth to support the desired communication capability is particularly difficult andinefficient using conventional spectrum management techniques. Channel assignmentsare fixed for extended durations, and those that are temporarily unoccupied are notavailable to other users without the intervention of spectrum management personnel.This places a great deal of overhead on an already burdened system, and the delaysincurred prevent a fully effective use of the spectrum resource.

Making more effective use of spectrum requires a dynamic approach to spectrum access.One approach, favoured for its suitability for monitoring and real-time correction ofspectrum fratricide, is to use a centralised controller to receive and process real-timespectrum requests using a policy- or rules-based engine. The use of a centralisedcontroller requires additional bandwidth for a common control channel, and this alsointroduces a security vulnerability. This approach is being investigated by TTCPpartners, and collaborative development and experimentation is part of the SpectrumEffectiveness Activity within TTCP C3I Technical Panel 2 (Communications, Networksand Dissemination).

Another approach is to make local decisions about spectrum occupancy based onobservations of the spectral conditions at the network nodes. An example of this isa policy-based spectrum access (PBSA) system, in which the occupancy is carefullycontrolled through the application of appropriate policies. These policies wouldbe generated at a central controller, and could be updated in response to evolvingconditions such as increased demand, but the requirement for real-time intervention ismitigated. In the AC3E Project, a PBSA system was implemented and demonstrated,leveraging earlier work at CRC on policy-based traffic management (PBTM) and inconjunction with the Arctic Communications element (Section 2). This is describedin Section 3.1.

Approaches to autonomous dynamic spectrum access (DSA), commonly referred toas ‘cognitive radio’ in the academic literature, typically require a dual-radio device,where one radio is used for sensing the occupancy of other channels (or bands) whilethe other is communicating. When interference is experienced, the communicatingradios switch to the best alternative channel. In a military scenario, this is a veryvulnerable approach, as radios can easily be herded around the spectrum, expendingvaluable bandwidth and battery power on overhead to exchange sensor information andlink establishment protocols, while achieving minimal useful throughput. Switchingchannels is a disruptive action that can have unintended, and undesirable, consequencesfor other spectrum users. Further, this approach is premised on the assumption that


the objective should be to obtain an interference-free channel.

In the preliminary R&D leading up to the AC3E Project, it was determined thatthe requirements for interference-free channels and, indeed, for distinct channelsthemselves are unnecessary. An alternative concept was developed, in which radionetworks would change frequency only as interference approaches an intolerable level,and then would seek to change their carrier frequencies only as much as necessaryto survive the effects of the interference. Several aspects of this approach have beenanalysed and simulated, and are described in Section 3.2.

In support of earlier work within TTCP [21], investigations were completed within theAC3E Project into generating an accurate picture of the spectrum use (Section 3.3).Such a capability would support a real-time spectrum management function, identifyingavailable frequency channels over specific geographic areas. This work showed that,in real environments, using only a small number of simple power sensors does notprovide a reliable spectrum occupancy map.

Good models of propagation and possible data throughputs are required to makethe most efficient use of the spectrum available. In the AC3E Project, analyses ofpreviously-collected propagation measurements were undertaken to support othercomponents of the project. In addition, a new measurement campaign, using multipleantenna elements at each of two transmitters and two receivers, was completedto obtain the critical spatio-temporal channel characteristics applicable to mobilenetworks. A preliminary analysis of these data sets was undertaken; additional workis required to gain further insights. This work is reported in Section 3.4.

3.1 Policy-based spectrum access

The policy-based spectrum access component of the AC3E Project was designed to fillthe ‘mission-specific’ link requirement of the NAN, Section 2, and also to demonstratethe effectiveness of using a policy-based approach to dynamically access spectrum.

The initial plan was to re-use the policy-based traffic management core of the NAN,reusing the architecture shown in Figure 2. However, interfacing this with the radioswas not practical, so a new architecture was designed, shown in Figure 4. The radiosused were Ettus N210 Universal Software Radio Peripherals (USRPs), connected tocomputers running a software modem written using a CRC-developed software radioframework. The radios operate on different carrier frequencies: for the NAN scenario,this emulates multiple available links to mobile network nodes, while for the spectrumaccess scenario the radios emulate a single device capable of selecting its operatingfrequency.


The policies in this policy-based spectrum access (PBSA) system are chosen to meetuser requirements of received signal quality and latency. The operator specifies theirdesired policy through a user interface, using a slider to select the preferred balancebetween the signal quality and latency. Limits on the acceptable ranges of link qualitymetrics can also be specified.

The system gathers information about the link quality by probing each of the channelsat configurable intervals. Short ‘PING’ messages are sent to obtain the signal-to-interference-and-noise ratio (SINR) and noise floor (NF) on each link, and also tomeasure the round-trip latency. These link quality metrics are used with the operator’sspecified values to compute an overall link quality score, which is used by the policyengine to select an appropriate link, i.e., frequency.

Figure 4: Emulated dynamic spectrum access system [6].

The policy engine receives the link quality inputs from the modems, and its link(frequency) selection is fed back to the modems. The policy engine acts as theinterface to a wide-area network (WAN), or other data source, by using a networktap device, known as a TAP driver, that intercepts the Ethernet frames, which areredirected by the policy engine to the selected USRP via CORBA (a standard forexchanging information between software written in different languages), rather thanbeing routed as IP packets [6].

The connections among the policy engine components are shown in Figure 5. As inthe NAN, a monitoring agent is used to gather situational awareness, in this case,link quality metrics, and these are fed into the decision-making module. The decision-making module also takes inputs from the user interface, which may be running ona different computer, and is therefore not shown in the figure. The decision-makingengine computes a link quality of service (QoS) score using the metrics returned fromthe modems, and applies the user policies to select a frequency. It then routes data


from the TAP interface to the appropriate modem and USRP, and it also passesnetwork traffic from the USRP to the TAP.

Figure 5: Policy engine components [6].

To prevent flapping, smoothing and hysteresis are built into the decision-makingprocess. The results of several consecutive observations are averaged to preventanomalous instantaneous observations causing unnecessary frequency changes; thenumber of observations to be averaged is configurable. Hysteresis is achieved byrequiring a change in quality score exceeding a minimum threshold before a change infrequency is made, and such a change is only made if there was no change immediatelypreceding.

To prevent ineffective exploitation of spectrum by implementing unnecessary andunpredictable frequency changes, the system does not change frequencies when abetter quality link becomes available, providing the current link quality is good enough.When no channel meets the required quality, the best one is selected, and the operatoris alerted to the fact that the quality is not met [6].

This system was demonstrated in December 2015 to DND and CAF stakeholders.Interference and delays were injected to show that, as the link quality deterioratesbeyond the level set by the policy, the decision-making module identifies that therequired standard is not being met, and uses its current link situational awareness toselect an alternative frequency.

Applications including digital voice and real-time video were demonstrated, to showthat the impact of the frequency change on the applications was imperceptible. Usinga voice call, for which excessive latency is unacceptable, it was shown that when theround-trip delay exceeded the specified limit, the frequency was immediately switchedto a link which had an acceptable delay and the best available signal quality.


This policy-based spectrum access system successfully completed the deliverables ofthe former Northern Communications project and, at the same time, demonstratedan important concept for robust dynamic spectrum access.

3.2 Spectrum sharing

Work in earlier projects has led to a focus on unmanaged spectrum access as a keyarea of research. Many modern waveforms are quite tolerant of interference, so theconventional spectrum management strategy, which strives to assign an interference-free channel, puts an unnecessary constraint on spectrum access. In contrast, conceptsdeveloped for interference-tolerant spectrum sharing put the onus on each user pair(transmitter and receiver) or network to manage its own spectrum access, withoutundue consideration for other users. This approach to dynamic spectrum access(DSA), colloquially known as ‘Mil-ISM’, is a parallel with the industrial, scientific andmedical (ISM) bands within the civilian-managed spectrum that are used by manyunlicensed services, including WiFi.

The absence of channel assignments in a Mil-ISM band allows for the elimination ofdefined channel occupancy. This means that users can emit in any piece of spectrum,varying both bandwidth and carrier frequency based on their needs and local conditions.As in conventional ISM bands, it is anticipated that power limits would apply. Inthe work in the AC3E Project, investigations focussed on fixed bandwidth systemswith variable carrier frequencies. In Section 3.2.1, core work on spectrum overloading,considering the impact of modulation and power partial band interference, is reported,as well as some theoretical analysis evaluating the trade-off between interference andbandwidth.

The concept proposed for users in the Mil-ISM band is that they will adapt theirfrequency occupancy by ‘sliding’ gracefully, rather than jumping from one channel toanother. Several aspects of this graceful sliding concept were explored in the AC3EProject, and are described in Section 3.2.2.

There are several advantages to this DSA concept. First, it should reduce the overheadof signalling exchanges among network nodes to coordinate frequency moves. Nodesmight exchange limited information about the rate and direction of their changes, orat the extreme, nodes may be able to infer frequency changes by observation. Forexample, as one node adapts its transmission frequency, the others should be able totrack the changes as though they were caused by Doppler shift. In this way, nodesexperiencing interference could draw the other nodes away from their own interferedfrequency range, in a sense, leading by example.


Second, nodes are able to sense the level of interfering power in the spectrum nearbytheir own signal using oversampling techniques. This eliminates the need for a secondreceiver to be used as a sensor, which would be required to measure the levels ofinterference in other parts of the band.

Third, this DSA concept prevents sudden changes in spectrum occupancy, therebyreducing the potential for instability. The robustness and resilience of the overallsystem-of-systems is thereby increased; preliminary work has confirmed this, althoughthe degree of advantage observed will depend on the impact of the duty cycles andrelative locations of the nodes in a network.

For networked radio nodes, decisions to change spectrum occupancy have to becoordinated across the network. A framework for achieving network DSA has beenproposed, using distributed cross-layer mechanisms to determine and disseminatedecisions about frequency changes.

Spectrum users may not have the same priority; when the spectrum is congested, itmay be advantageous for some users with lower priority information to yield some oftheir occupied spectrum to compatriots or allies with higher priority requirements.There was some preliminary investigation of this altruism concept in the AC3E Project,Section 3.2.3.

To support the concepts proposed for spectrum sharing, such as altruism, a spec-trum labelling technique was proposed, which embeds a very low rate signal in theuser’s emitted signal, which can be identified by other spectrum users. In support ofsimulations, this concept was partially implemented to determine whether synchro-nisation and detection were achievable in real systems. This work is summarised inSection 3.2.4.

When each node is equipped with multi-element antennas, it has been proposed inthe academic literature that multiple links can co-exist by spatially aligning theirinterference. This technique is specifically aimed at dense multipath environments,such as urban areas, where high rate communication is typically challenging, butmay be improved using spatial diversity. Work in earlier projects has shown thatthese theoretical techniques are not achievable in real environments, where imperfectchannel knowledge is inevitable.

In the AC3E Project, a robust, distributed approach to interference alignment hasbeen proposed and evaluated, which uses a manageable amount of overhead signallingand tolerates the impact of imperfect channel knowledge. A summary of this work isprovided in Section 3.2.6, and it was supported also by experimental measurementsdescribed in Section 3.4.2.


Although a great deal of research has been published in the academic literatureproposing and evaluating schemes for DSA, there is very little practical work reportedon implementing these in real radios. In particular, medium access control (MAC)protocols for supporting DSA have not been adequately investigated. The AC3EProject included a study of several existing protocols to determine which featuresshould be incorporated in an effective MAC protocol for DSA networks, Section 3.2.5.

3.2.1 Spectrum overloading

As noted above, many modern waveforms are able tolerate some degree of interference,and the lack of defined channels allows the signals to be placed where they mayexperience or cause partial band interference.

The principle of overlapping waveforms is illustrated in Figure 6, where S(f) is thepower spectral density (PSD) of the desired received signal, which has carrier frequencyfc and bandwidth B = 2/T where T is the baud interval. I(f) is the PSD of thereceived interference from a signal with carrier frequency fint and also has bandwidthB, for simplicity. Δf is the separation between the two carriers.

frequency

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Figure 6: Frequency domain representation of overloading spectrum.

Initial studies considered the tolerance of various modulations, specifically, binaryphase-shift keying (BPSK), binary partial- and full-response continuous phase mod-ulation (CPM). It was found that partial-response CPM was particularly resistantto partial-band interference, with insignificant degradation of its bit error rate atoverlaps up to 50% of bandwidth (Δf = B/2, or Δf · T = 1) for signals received atthe same power [7].

Results reported in [7] also showed the impact of heterogeneous partial-band inter-ference, for example, a (filtered) BPSK user is less sensitive to interference from apartial-response CPM signal than other interfering modulations considered.


This preliminary investigation concluded that the choice of modulation is a criti-cal component in conserving spectrum, perhaps more significant than the optimalallocation of frequency neighbours [7]. However, this work did not consider the robust-ness of carrier synchronisation and timing recovery under the impact of partial-bandinterference.

Further work in this area led to the development of algorithms for the adaptation ofcarrier frequency in response to interference [8], which are discussed in Section 3.2.2.

In this stage of the AC3E Project, the bit error rate was used as the only input to thedecision whether to adjust the frequency or not. The SINR was also considered later [8],and cross-layer parameters were investigated for networked communications [1]. Theseare discussed in Section 3.2.2.

A separate study into spectrum overloading used an information theoretic approach toevaluate the total capacity supportable when two pairs of users co-exist in a definedcircular area [9]. The work was based on capacity, which is an information theoreticmeasure based on ideal assumptions and is an upper bound, typically very loose, onachievable throughput. The analysis showed that, at low and moderate SNRs, thesum capacity is maximised, on average, when the two pairs of users share the fullavailable spectrum bandwidth. At high SNRs, however, the total capacity would bemaximised by letting each pair of users each access only half the available spectrum.The threshold at which this differentiation happens is dependent on the size of thearea, the users’ transmitter powers and the assumed propagation model.

This theoretical study gives a fairly intuitive result, based on the assumptions inherentin a capacity analysis, specifically, that both the signal power and its informationcontent are uniform across the bandwidth. A binary result is therefore expected:either the two users’ signals should completely overlap, or they should not overlap atall. In practical communication systems, these assumptions are not met, thereforefurther analysis is required to address this problem fully.

3.2.2 Frequency adaptation

The ability of digital waveforms to provide the desired performance when they ex-perience partial-band interference was demonstrated by simulation, as discussed inSection 3.2.1. To extend this preliminary work to a mobile wireless environment,adaptive algorithms designed to respond to dynamic propagation and interferenceconditions were investigated.

The system approach at the focus of this work is graceful frequency adaptation, in


which a radio’s spectrum occupancy is smoothly adjusted, rather than ‘jumping’ fromone channel to another. This concept arose from an earlier project, where it wasnoted that the overhead costs of sensing and exchanging sensed information wereexcessive in a mobile network. It was conceived that small, smooth changes in carrierfrequency would require minimal exchange of information, as each receiver might trackthe frequency offsets automatically. Further, no secondary receiver would be necessaryfor channel sensing, as observations about local interference could be obtained fromoversampling in the primary receiver.

In contrast to most published literature in this area, the objective of this approach isthen for each user to automatically adjust its spectral occupancy to accommodateits own tolerance for interference. As the environment of interest is dynamic, apreliminary assumption in this approach is that interference is gradually increasingand decreasing, based on the location of the interferer, as well as its own changingfrequency, therefore sudden frequency adaptations are not required.

There were several aspects to the R&D in this area; changes to time and personnelallocation within the project did not allow them to be investigated as far as originallyintended, or for them to be integrated into a fully networked concept. Nonetheless,the work that was achieved shows that this concept has promise as a robust andresilient approach to mobile networked communications.

Adaptation based on physical layer parameters

Following the work reported in [7], the first steps toward a distributed frequencyadaptation mechanism were reported in [8]. As in the previous work, heterogeneouscombinations of PSK and CPM users were considered as the signal and interferer ofinterest, using the overlap condition illustrated in Figure 6.

In this investigation, the decision by pairs of users to adapt their frequency is basedon physical layer parameters, specifically the uncoded bit error rate (BER) or thesignal-to-interference-and-noise ratio (SINR). A simple sliding algorithm changes thepair’s carrier frequency away from the interferer when the performance parameteris below a prescribed threshold, and leaves it unchanged when the performance issatisfactory.

It was shown that a trade-off is necessary between the accuracy of the performanceparameter estimate, i.e., the information provided to the decision-making algorithm,and the responsiveness of the system, and a smoothing approach was used to supportthis trade-off.


Simulations showed that this simple sliding algorithm, using either physical layer pa-rameter, was able to respond to different interference powers; convergence was slightlyslower when the interference power was lower because the performance parameter willnot necessarily fall below the threshold for every observation.

The impact of the step-size was also evaluated, and the results were as would beexpected: the response gradient was slower for smaller step sizes, but the finalconvergence resulted in smaller final spectral offsets. This suggests that an adaptivestrategy, using larger steps when the performance is very poor and smaller ones as itapproaches the desired level, would be optimal.

For more than two user pairs, the performance of each receiver is affected by multipleinterfering signals of different received powers, as illustrated in Figure 7(a), wheremultiple user pairs ui, i = −M, . . . , M , co-exist. The resulting power spectrum at thereceiver of pair u0 is illustrated in Figure 7(b), where fi, i = −M, . . . , M , indicatesthe users’ carrier frequencies.

u-1

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Figure 7: Multiple user pair scenario (modified from [10]).

Simulations were used to evaluate the trade-offs between user performance reliabilityand total spectrum resources. Two adaptive spectrum overloading strategies wereused: uniform carrier frequency separation, and flexible separation obtained usingthe simple algorithm described above. In addition, the impact of reducing the totalbandwidth occupied by optimally ordering the users was evaluated for each adaptivestrategy.

Figure 8 shows these trade-offs for five user pairs (M = 2) using BPSK or partial-response CPM. The x-axis is the average bandwidth per user, and the y-axis is theempirical probability that the threshold BER outage of 5% is achieved.

These results show that the flexible strategy gives gains in spectral effectivenessrelative to using a uniform distribution of carriers. This makes sense in a dynamic


environment, as the interference experienced by different user pairs will depend ontheir relative locations. More significantly, there is a substantial gain in spectraleffectiveness when the reduced-bandwidth (‘red-bw’ in the figure labels) scheme isapplied to enforce an optimal order on the spectrum occupancy.

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Figure 8: Trade-offs between user reliability and spectrum resource usage [10].

Allowing the users to adjust their own carrier frequencies to satisfy their desired linkqualities can be achieved simply, and provides significant potential improvements intotal spectrum efficiency. This is particularly important in heterogeneous environments,as it has been seen that different modulations support different spectral densities.

There will be occasions where significant gains may be made by re-ordering thespectrum occupancy of the users, i.e., enabling users to ‘jump’ over other users inthe spectrum to escape local interference conditions. Further work is required tofind mechanisms to achieve this in an efficient way, and to determine the cost-benefittrade-offs.

Robustness, complexity and resilience

Most analysis of dynamic spectrum access addresses first-order performance, i.e.,standard QoS parameters such as bit or packet error rate, SINR, data throughput,etc. This work was focussed on evaluating the second-order performance of dynamicsystems (frequency-adaptive mobile users) and systems-of-systems (collectives offrequency-adaptive mobile users).

In this work, extensive simulations were performed using large numbers of mobileuser pairs, changing their operating frequencies independently of one another, using agraceful adaptation strategy. The analysis focussed on robustness, complexity andresilience.


The simulations and evaluation used the capacity as a proxy for radio performance.However, in contrast to the work reported in [9] and discussed in Section 3.2.1, thepower spectral density profile of each user was assumed to be triangular in linearunits, which gives a log occupancy similar to those illustrated in Figures 6 and 7(b).

The simulation model used N pairs of nodes randomly placed in a circular field-of-view,where the transmitters and receivers were separated by a random but fixed distance.A circular mobility model was used, illustrated in Figure 9(a), which shows the lociof the transmitters colour-coded to indicate their carrier frequencies. In this figure,the frequency occupancies are channelised into six channels; the distribution of thenumber of channel bandwidths moved in each update is shown in Figure 9(b), alongwith those for graceful frequency adaptation with maximum sliding offsets 1/4 and1 channel bandwidths and the full available bandwidth. Even when the adaptationis allowed to range across the whole available spectrum, the median offset is 15% ofa single channel bandwidth for all the sliding modes, indicating that restricting thefrequency range of the graceful sliding strategy has a limited impact most of the time.

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Figure 9: Characteristics of dynamic system with N = 50 user pairs.

Robustness The robustness of the dynamic system, or the system-of-systems, canbe evaluated using the change in capacity of the user pairs, or the change in sumcapacity, respectively, between one time interval and the next.

Simulations showed that, at low user densities (N = 50), the variation in sum capacityfrom one time interval to the next was greatest for the case of fixed frequencies, andthe overall capacity was lower for this mode. The channelised DSA mode showed theleast variation (increase or decrease) from one interval to the next, and also had (by asmall margin) the highest total capacity.

At higher densities, even though the interval-to-interval variation in capacity of


individual user pairs remained lowest for the channelised mode, the variation in thesum capacity was largest for this mode. These results are illustrated by the cumulativedistribution functions (CDFs) of capacity change in Figure 10. This observationsuggests that scenarios may tend to accumulate large numbers of pairs that eitherlose or gain, which is not indicative of a robust system.

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Figure 10: Robustness of dynamic system with N = 200 user pairs.

Complexity When there are many dynamic components in a system, even wheneach is adapting according to simple rules, the overall system-of-systems may bestructurally complex. There is not a single common definition or metric for complexity,but for information sources, entropy-based measures such as the sample entropy areoften used. They measure the degree of randomness, or, conversely, the degree oforder, within the data.

In this work, a multiscale entropy analysis [22], based on sample entropy, was used toevaluate the complexity of the dynamic system; this enables the analysis to accountfor structures in the system that are longer than a single sample interval. Analysisof the simulation results showed that the capacity achieved by individual node pairsexhibits complex characteristics, although there was a tendency for this to tend towardsmaller scale correlation as the density of users increased. The total system capacityfollowed a similar trend, but the channelised and full bandwidth sliding strategy hadhigher complexities at all scales as the density increased.

More detailed analysis of the complex dynamics of these systems and systems-of-systems may give insight into the degree of control or oversight that should beimplemented to enhance their spectrum effectiveness and to provide appropriate levelsof monitoring to detect and correct inefficiencies and anomalies.


Resilience The system resilience was evaluated by inserting a disruptor into a staticscenario, as illustrated in Figure 9(a), in which the user pairs had already convergedto their local preferred spectrum occupancy. The system transition is illustratedin Figure 11(a), where the function F could be the sum capacity or capacity of anindividual node pair. The system is in a converged and steady state at time t0, and td

refers to the instant immediately after the disruption occurs. The resilience is thenmeasured over the interval td ≤ tr ≤ tf , where the system has reached its final steadystate by time tf . An appropriate metric for resilience is given in [23]:

R(tr) =F (tr) − F (td)F (t0) − F (td)

. (1)

Figure 11(b) shows the distribution of resilience (shown as a percentage) in the totalcapacity, computed after the system has converged, i.e., tr = tf). The results showthat there is a greater range of variation in the channelised case, including a largerdecrease in final throughput, while the graceful sliding case with a maximum slide of1/4 channel bandwidth has the most resilient response, and also experiences the largestpercentage gains after the disruption. The results also indicate that the shortest rangegraceful sliding mode has the fastest recovery, and the channelised has the slowest.

(a) System state transition

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Figure 11: Resilience of dynamic system.

One of the significant advantages of the short range graceful sliding mode is illustratedin Figure 12, which plots the frequencies changes (y-axis) over time (x-axis). Eachnode pair is assigned a unique colour, and those that do not change frequency areomitted from the plot. The X on the y-axis indicates the frequency of the disruptor.

In this example, the channelised case (panel (a)) continues to ‘ring’, as two node pairscontinue to switch back-and-forth between two channels. All other nodes remain static


in frequency occupancy, and hence are not shown. For the mode where each node’sfrequency occupancy can be anywhere within the prescribed bandwidth (panel (b)),there is also an extended duration of adaptation that engages an increasing number ofnode pairs, although it is not ringing and will eventually settle. In the case of gracefulsliding over a range of one channel bandwidth (shown in panel (c)), there is only asmall number of node pairs involved at each time interval, and the system stabilisesafter only four updates.

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Figure 12: Frequency updates after disruptive event.

This preliminary work shows that there is an inherent robustness and resiliencein the graceful sliding approach, which means that most users experience fairlysmooth dynamics in both link quality and frequency occupancy. As noted above,this sliding approach does suffer from possible ‘trapped’ nodes, which are unable toevade significant interferers on both sides. This might be resolved by the inherentdynamism in the system, resulting from the mobility and spectral adaptation ofall the nodes. Alternatively, an ‘escape’ mode might be incorporated, in which thenode pair jump to another part of the available spectrum, either blindly or using apre-scanning capability. As noted previously, there is scope for further work in this


area, to determine the effectiveness of different escape mechanisms.

Network coordination

When the ‘network’ is more complex than a single user pair, i.e., when there are multiplenodes inter-communicating, the spectrum access problem becomes significantly morechallenging. Frequency selection decisions must be coordinated among the nodes,otherwise the network may become unstable, routes may fail or nodes may becomeisolated.

Figure 13: Network coordination framework [1].

The work reported in [1] focussed on the development of a framework for dynamicspectrum access in multihop networks using the graceful frequency adaptation strategy.The framework components are summarised in Figure 13.

The proposed network architecture uses TDMA-based scheduling, with intervals forbeaconing (network discovery) as well as sensing and reporting (spectrum adaptation).To address the inefficiencies of the network protocol stack, a cross-layer protocolarchitecture was proposed, shown in Figure 14, which enables the sharing of informationbetween adjacent layers, and provides an integrated control function, [1]. Each ofthe network functions is implemented by specific protocols; these, along with theassociated controllable parameters and information available for sharing with otherlayers, are summarised in Table 1.

Distributed mechanisms were proposed within this framework to support coordinatedgraceful frequency adaptation within a network. Updating functions at each nodeprovide the ‘Node Profiling’ component in Figure 13, and a nonlinear weightedcombining function supports a voting scheme for deciding the new frequency to beused across the network, i.e., the ‘Network Adaptation’ component.


Figure 14: Cross-layer protocol architecture [1].

This work was supported by simulations demonstrating the performance of the al-gorithms for different operating parameters. These simulations showed that theframework provides a good basis for designing and implementing a graceful frequencyadaptation strategy as a means to achieve robust and effective dynamic spectrumaccess in radio networks. Further work is required to study the ‘Information Dissemi-nation’ component in Figure 13, in particular, to evaluate the costs of signalling andcontrol overheads [1].

3.2.3 Altruism

When many users are sharing a limited spectrum resource, there will be a tendency to‘grab’ bandwidth and maintain occupancy to ensure it is available when needed. Theacademic literature in social behaviour and evolutionary theory suggests that there arenet advantages to exhibiting altruism, i.e., making a held resource available to othersin need. In the spectrum context, this could be a model for giving up, or lending,spectral bandwidth to other coalition partners, when their need for it is greater. Thissuggests a priority scale of information value; for example, some situational awarenessor command and control signalling would take priority over routine downloading ofnon-real-time data files. The spectrum labelling concept, Section 3.2.4, was proposedas a method for making this ownership and priority known without the vulnerableexchange of information over a control channel.


Table 1: Cross-layer controlled parameters and shared information [1].

Function Mechanism Controllable Shareableparameter information

User application Adaptive bitrate Source rateEnd-to-end delayDelivery ratio

Error control ARQ-based Retry limitPacket error rateRetry count

MAC scheduling TDMA-based Allocated slotsRx traffic rateTx traffic load

Datatransmission

Adaptive radio Radio modesSINRInterference

The work undertaken in this area used a model of resource sharing based on evolution-ary theory, in which spectrum would more readily be given by user A to user B if theirrelationship is close, on the basis that it is likely that B’s gain is to A’s advantage. Onthe other hand, if C has a more distant relationship to A, the information for which C

wishes to use the spectrum must have a larger priority differential. If A has its ownhigh priority information to send, it will act selfishly and not share its spectrum evenwith close relations.

This approach showed potential, and the preliminary results showed that there areindeed scenarios where it can be determined that it is likely beneficial to share theresource. Further analysis and experimentation is required, however, as its applicationrequired a reasonable model of the costs of exchanging information (in a network,these include the overheads of routing, packet formation, etc.) as well as the prioritiesand relationships of the different spectrum users.

From a spectrum management perspective, it would be important to understand whattypes of spectrum sharing policies would be appropriate in different scenarios, andthis is one approach to achieving analytical insight into that problem. Due to timeconstraints, this work has not yet been completed; however, it shows promise as abasis for understanding whether, and when, spectrum resources should be shared withcoalition partners.

3.2.4 Spectrum labelling

One of the challenges of heterogeneous users operating in an unmanaged spectrumband is that each network has no knowledge of the others, and there is no way todetermine priority of access.


In an earlier project, a spectrum labelling concept was proposed, whereby a verylow rate identification label could be superimposed on any transmitted signal, at theemitter. This label could be detected and decoded by any other user, without havingany additional information about the host signal such as modulation or waveform.

The spectrum label could identify national ownership, facilitating spectrum coordina-tion among users of the same nation or close allies, and/or information priority. Thiswould facilitate the ‘lending’ of spectrum by a lower priority user to a higher priorityuser, Section 3.2.3, without necessitating additional control information exchange.

The principle of spectrum labelling is to pass a very low rate of side information,available to all spectrum users, without using additional spectral bandwidth, reducingthe host’s data rate, or significantly affecting the reception of the host signal.

The approach proposed is to embed a low power label within a host signal, as illustratedin Figure 15. The signal could be detected noncoherently without requiring detectionof the host signal, and would be robust to time- and frequency-selective fading. Thecontents of the label would be low rate and heavily coded, for example using ratelesscodes [24], and repeated continually.

For modern waveforms, this label could be easily integrated into the transmitter, andfor legacy equipment, it could be added in the RF chain, for emission from the sameantenna.

Figure 15: Spectrum label (red) embedded in host signal (blue).

This concept was simulated in software, using sequences spread in time and optionallyin frequency. It was shown that using a trick in detecting the spreading sequences,the data bits can be recovered even in quite severe fading. As expected, there is somedegradation to the host signal, resulting in an interference error-floor; the severity of


this depends on the host signal and, for a low-enough power label, it is likely to bebelow a level that impacts application performance.

A partial proof-of-concept was implemented on several Ettus N210 USRPs using theGNUradio software-defined radio framework [11]. This work had the objective oftesting the carrier and clock recovery of the label when it is embedded in a hostsignal. Using this implementation, different host-to-label bandwidth and signal powerratios were tested, and it was demonstrated that their recovery was quite robust. Forexample, Figure 16 illustrates the received signal constellations for a BPSK labelembedded 32 dB below the QPSK host signal, with a bandwidth 1/20th that of thehost. At this low relative power level, there is minimal degradation to the host, andthe label signal is still detectable using coding and spreading.

(a) Host signal (b) Label signal

Figure 16: Received constellations for host-to-label power 32 dB and label signalbandwidth 5% of the host signal bandwidth.

The spectrum labelling concept has been shown to have strong potential as a solution toproviding some identifying information about users in a shared spectrum environment.There is still some work to be done, requiring more complete prototyping and additionalsimulations to specify appropriate parameters and performance expectations.

3.2.5 MAC protocols

Good coordination of spectrum access amongst heterogeneous users is required toreduce interference for effective dynamic spectrum access, and small managementoverheads are necessary to reduce wastage for efficient spectrum use. Both of thesebehaviours require an appropriately-designed medium access control (MAC) protocol.

A study of several MAC protocols was undertaken to assess their behaviour and their


effect on heterogeneous network performance, as a first step in developing a frameworkfor systematic MAC evaluation.

The study, reported in [12], considered circuit-based and packet-based multiple accessschemes. In the first, the focus was on frequency, time, code or space division multipleaccess. In the latter, three groups, namely contention-free, contention-based andhybrid schemes, were considered. A variety of metrics was introduced to compare theprotocols’ performance in different scenarios.

The report also reviewed the architecture and implementation of the standardisedMAC protocols for LTE, WiFi, the tactical global information grid (GIG) widebandnetworking waveform (WNW), and the enhanced position location reporting system(EPLRS).

The design of context-aware MAC protocols was identified as a particular challengefor future S&T. These MACs are needed to support the efficient and effective use ofspectrum resources, providing the desired quality of service while optimising networkresources by adapting radio parameters, including carrier frequency and bandwidth,and application parameters such as traffic load and network topology.

3.2.6 Interference alignment

Interference alignment (IA) is an approach to spectrum sharing based on a coordinatedspatial coexistence of users’ signals. Multipath diversity, such as that observed in anurban environment, can be exploited to improve the combined spectral efficiency ofseveral users.

Figure 17: Interference alignment for multiple pairs of users in a multipathenvironment.

Typical IA scenarios involve several pairs of users operating simultaneously in the samefrequency channel, all with antenna arrays. It is primarily of interest in a multipath


environment, such as an urban region, where transmitted signals are blocked by, andreflected from, buildings and other objects, Figure 17. It requires an exchange ofinformation among the pairs, and is therefore particularly applicable in a networkedenvironment, where the coordination and networking overheads can be combined.

The concept of IA is that each transmitting user applies complex weighting to theelements of the array, to ‘steer’ the emitted signal in such a way that its intendedrecipient receives a sufficiently strong signal, while other receivers in the area, forwhom the signal is interference, receive only a low power. To maximise the potentialof spatial diversity, this transmission steering does not generally result in a singledirectional beam, but will include multiple directional signals with different phasesand amplitudes, depending on the spatial characteristics of the link between thetransmitter and its intended receiver.

Theoretically, in a sufficiently rich multipath environment, it is possible for 2K − 1users with K antenna elements in their transmitter and receiver arrays to all achievean interference-free signal. Thus, it is theoretically possible for seven pairs of userswith K = 4 antenna elements, arranged linearly and spaced by at least one-half of awavelength, to simultaneously achieve a full throughput link with no interference.

This theoretical result relies on the impossible assumption that all transmitters and allreceivers in the system (14 terminals in the example above), or a centralised controller,must have perfect channel information of not only their own links, but all other linksin the network. That is, all (2K − 1) × (2K − 1) links must be known, where eachlink is described by a K × K complex matrix. Even in the static case, receiver noisemakes this unachievable. When there is any mobility, either of the terminals or withinthe environment, the amount of overhead that must be continuously exchanged tomaintain reasonably up-to-date, but noisy, channel state information is overwhelming.

A robust distributed, quantised IA algorithm requiring only limited feedback fromreceivers to their own transmitters has been proposed and evaluated [13, 25]. Ineach frame, each receiver determines which of a pre-defined set of array weights itwould prefer from each of the interfering transmitters, as well as an indication of theinterference power, and feeds this information (which requires only a few bits) backto all of the transmitters. Each transmitter then generates an array weighting for thenext frame by combining these pieces of information, which relate to the interference itcauses to all the other receivers. Cooperation among the receivers is achieved becauseeach is able to ‘overhear’ the messages fed back by the others.

Simulations were performed using standardised simulated mobile, non-line-of-sighturban environments, [13]. It was shown in that this algorithm was more robust overthe range of mobile speeds (1–40 km/hr) than other leading algorithms, and that useful


signal-to-interference ratios were achievable for significant portions of the simulations.

This work provided confidence that there is potential for spectrum sharing usingIA schemes for mobile scenarios, even though it is clear that the theoretical gainsare unachievable. This would enable several network links to co-exist in time andfrequency, increasing overall throughput and reducing network delays. Further workwould use a cross-layer adaptation to dynamically assign TDMA slots as the usersmove, by selecting links to co-exist based on (near) real-time evaluation of their spatialco-existence potential.

Experience within this research program has shown that real channel conditions requireadditional considerations to design effective signalling strategies, due to the limitationsof statistical models. Progress towards this was made with a measurement campaigndesigned to obtain spatial channel characteristics on different links simultaneously.This campaign is described in Section 3.4.2.

3.3 Shared spectrum situational awareness

The concept of a radio environment map, also known as an RF common operatingpicture [21], is to provide a description of the measured or estimated RF occupancyover a range of frequencies within a given geographic area. This capability could beused to support real-time dynamic spectrum management and channel assignment.

While conceptually simple, there are several practical challenges, including the prop-agating environment itself, the quality and type of data provided by the sensors,and the overheads required to collect the data from sensors in the region (this wasconsidered in an earlier project, reported in [26–28]).

In a complex environment, a more dense network of sensors and more detailed data,such as directional power, may be desirable; however, this results in much higheroverheads to collect the data. It can be expected then, that at some point, thebenefits of using dynamic channel assignment based on a radio environment mapmay be outweighed by these costs. Navigating this trade-space is impossible withoutdefinitions of the resolution (in space) and accuracy (in power level) that are requiredfor this to be a useful capability.

The work in the AC3E Project focussed on addressing the impact of the complexpropagation conditions. To this end, an RF ground-truth was established using ahigh-quality propagation prediction tool, COVLAB, developed by CRC. The terrainfor this region is shown in Figure 18. This is used to determine power levels ata specified resolution, for three emitters with isotropic antennas mounted at 3 m


above ground level, operating at 100 W EIRP at a carrier frequency of 300 MHz,as illustrated in Figure 19(b). This ground-truth map is far more complex than thetypical ‘flat-earth’ model, Figure 19(a), that is typically used for R&D in spectrumoccupancy mapping.

Fitzroy Harbour

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Figure 18: Terrain map, West Carleton area.

(a) Idealised radio map

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Figure 19: Spectrum occupancy characteristics, West Carleton area.

Power sensors were simulated as deployed randomly across the region, and theiroutputs were processed at a central hub. A common approach to the problem ofgenerating a radio environment map is to geo-locate the emitters and then super-imposea propagation model to estimate the spatial RF power. However, it is well-knownthat geo-locating multiple (in this case, an unknown number of) emitters using onlypower information tends to produce inaccurate results. This is exacerbated in acomplex propagation environment, where the pathloss experienced by signals emittedin different directions can vary widely.


Static sensors provide only a single spatial sample of power, which may be quiteunrepresentative of other samples very close by. It has been observed many times inchannel measurement analysis (as in Section 3.4) that the power level can vary bymany deciBels over a distance of less than one wavelength. Mobile sensors provide adegree of spatial averaging, which can be advantageous, but they can make the datacollection process more challenging. In this analysis, the effects of localised multipathfading are neglected, which is equivalent to assuming the sensor obtains an averagepower over an area covering several square wavelengths.

It was determined that the relevant objective is to identify the regions within thearea of interest in which the power level is above (or below) a given threshold, so thatfrequency assignments can be made without causing unacceptable levels of interference.For this example, the threshold was set at -80 dBm.

A method based on belief propagation has been developed that allows uncertainty tobe taken into account. In this problem, uncertainty in the collected data arises due tothe propagation environment, the number, powers and locations of the emitters andthe accuracy of the sensed information. The output is a belief, or level of confidence,in the spectrum occupancy level, measured from zero (no belief the power level exceedsthe threshold) to one (complete belief the power level exceeds the threshold). One ofthe advantages of this approach is that cells can be updated independently, making itpossible to ‘zoom-in’ on a particular area, or to maintain different refresh rates ondifferent portions of the map, e.g., those where the belief is inconclusive, or whereusers need new spectrum assignments.

The details of the technique are given in [14]. Example output belief maps are shownin Figure 20(a) and (b), where the 100 random sensor locations are indicated asdark cells. In the example in Figure 20(a), the belief-based spectrum occupancy mapis quite good, although the impact of the Eardley Escarpment, running across thenorth-east portion of the region, is not captured. However, in another example with adifferent placement of the 100 sensors, in Figure 20(b), the belief map is quite poor.

Some of the additional uncertainties that were not considered in this work, but whichmay further degrade the quality of the output, include partial duty-cycles of theemitters, when each sensor may capture a different portion of the transmission cycle.Similarly, if there are multiple emitters in a local region, e.g., a network of users, theeffective average powers and emitter locations will vary depending on the sensingcycles. The dependence on the location of sensors is also problematic, unless they canbe deployed intentionally to complement existing data sources.

This work showed the difficulty in generating a reliable spectrum occupancy map inreal environments with limited sensed data and many uncertainties.


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Figure 20: Belief-based spectral occupancies.

An alternative approach is to use smarter sensors that are able to provide higher qualityinformation about their observations, for example, modulation detection and directionfinding. This results in both a greater acquisition cost and a greater bandwidthand power cost to collect the increased data volumes. The Military Digital AnalysisSystem (MiDAS) is an example of a sophisticated radio monitoring system, which iscurrently in use by the CAF [29].

Other work is ongoing in this area. Commercial systems with some related functionalityare now available, including LS Telcom’s Observer [30], which has limited spectrummapping capabilities based on detailed sensor observations. DARPA’s AdvancedRF Mapping (RadioMap) program [31] is in its third phase, with a contract toLockheed Martin to develop a system for military services. CRC is also developingspectrum environment tools as part of its Spectrum Environment Awareness GrandChallenge [32].

3.4 Spectral efficiency

Experience through a series of research projects has demonstrated the importance ofgood channel models and simulations in designing signalling strategies. When thesignal design and receiver signal processing is not well-matched to the actual channelbehaviour, performance degrades, resulting in a reduced throughput and hence loweroverall spectral efficiency.

In the AC3E Project, data sets from three measurement campaigns were analysedto investigate the properties that are key to efficient communications. Two of theseanalyses (multi-frequency and air-to-ground) used data collected near the end of the


previous project, but the analyses are new within the AC3E Project.

The measurements were all performed using the CRC MIMO channel sounder [33],which uses antenna arrays of Nt elements at the transmitter and Nr elements at thereceiver to measure all the links in the Nr × Nt multi-input multi-output (MIMO)channel simultaneously. This sounder was developed in the early 2000s, and operatesat frequencies up to 2.4 GHz.

Measurements at frequencies in different parts of the UHF band were used to evaluatethe requirements for cross-layer adaptation that DSA radio would have to satisfy, tooperate over a wide frequency range, this analysis is discussed in Section 3.4.1.

In an earlier project, the sounder’s capabilities were extended to operate as a soundingnetwork, with multiple transmitter terminals and multiple receiver terminals [34].In the AC3E Project, that capability was used in an urban environment, providingthe first known mobile networked measurements of spatial channels, as described inSection 3.4.2.

As part of a TTCP collaboration with the US Air Force Research Labs (AFRL), amini-sounder was built that could be loaded into one of AFRL’s unmanned aerialvehicles (UAVs). Analysis of data from this measurement campaign provided insightinto what is achievable for range extension using an aerial node exploiting spatialdiversity; this is summarised in Section 3.4.3.

3.4.1 Multi-frequency measurements

The early vision of cognitive radio, or (more accurately) DSA-capable radios, is wellarticulated in [35], where radios are assumed to have the capability to self-tune acrosslicensed and unlicensed bands, i.e., a wide range of frequencies. While this verywideband functionality poses challenges for the RF front end and for the channelsensing process, it also subjects the radio to potentially very different propagationconditions.

For mobile communications, operation across a wide range of frequencies is a partic-ular challenge, because the temporal characteristics of the operating conditions arefrequency-dependent. This was studied by further analysis of data collected in earliermeasurement campaigns [36].

Measurement data sets were collected using the CRC MIMO channel sounder [33] at370 MHz and 2 GHz, representing the extremes of the UHF band, in urban Ottawa.Data collected at 915 MHz was found to have interference levels that were too high


to perform reliable analyses. The transmitter terminal was housed in a trailer, witheight antenna elements mounted on the roof, which was parked at the side of thestreet, Figure 21(a). The receiver terminal was mounted in a van, again with eightantenna elements on the roof, which was driven around the neighbouring streets, onnon-line-of-sight routes, Figure 21(b).

(a) Static transmitter (b) Mobile receiver

Figure 21: CRC MIMO channel sounder.

An analysis of the temporal characteristics showed that the temporal and frequencycorrelation characteristics of the two frequencies varied by frequency and by localenvironment (mid-block and intersection), [15]. These characteristics also differedfrom those predicted by standardised channel models—this was not a surprise, aschannel characterisation work in earlier projects repeatedly showed that theoreticalmodels are inadequate for assessing actual measured performance. The focus of thework in [15] was to illustrate that analyses of these types of channels is inherentlylimited by the lack of wide-sense stationarity over relatively short distances, and bythe fading characteristics in time and frequency, and therefore the inadequacy ofmodels is inevitable.

One of the advantages of using measured data is the ability to evaluate signal processingstrategies under repeatable, real channel conditions. The data sets described abovewere used to evaluate typical cross-layer adaptations required when dynamic spectrumaccess radios alter their operating frequencies across the UHF band [16]. The analysisbuilt on earlier work in spatial-diversity, in which the deleterious effect of the changingchannel response on system performance was evaluated [37,38].

The simulated model used transmitted packets consisting of training or pilot sequencesand data, which was coded at different rates using a spatial precoding scheme developedearlier in the program [39]. The time-series of measured data enabled the impacts ofchannel variation over the length of the packet, as well as over the interval betweenthe collection of channel estimation information in one packet, and its use to adapt


the transmitter parameters in the next. For spatial diversity systems, earlier workhas shown this adaptation of transmitter parameters is key to maximising spectralefficiency [37].

It was shown that the variation of the channel characteristics was greater at the higherfrequency, resulting in larger errors between the channel estimates and the actualchannel conditions. This impacts the length of packet that can be supported at agiven error performance and, equivalently, the retransmission rates. These increaseddegradations at higher frequencies are the result primarily of faster multipath fading,but it has also been observed that there are some difference in spatial diversity acrossthe UHF band, which is attributed to the reflective properties of objects such asbuildings in the environment [16].

The analysis of system performance showed that different cross-layer trade-offs arerequired at different frequencies, and in different environments. In general, shorttraining sequences provide a higher net throughput when the packets are very shortand the code rate is low. As the packet length or the code rate increases, a moreaccurate estimate of the channel is required, so a longer training sequence is necessary.This effect is more pronounced at higher frequencies, where the temporal variation ismore rapid. For example, the optimal packet length at 370 MHz was more than twiceas long as at 2 GHz, and a medium length training sequence, balancing overhead andaccuracy, was the best choice [16]. The cross-over points are dependent not only onfrequency, but also on location, indicating the advantages of a system that adaptsautomatically to its local operating conditions.

This work showed that DSA alone is not sufficient to obtain good mobile radioperformance, particularly in challenging environments such as urban areas. When theoperating frequency is changed substantially, for example from the NATO UHF band(225–400 MHz) to the ISM band (2.4 GHz), the waveform parameters must also bechanged or the system performance will suffer significantly.

3.4.2 Multi-node measurements

One of the unique features of the CRC MIMO channel sounder [33] is its ability to beconfigurable as multiple transmitter and receiver arrays. This was initially tested in aprevious project [34], but coordinating a full-scale measurement campaign requiredmore planning and resources.

For the AC3E Project, measurements were made using two transmitters and tworeceivers, each with four-element antenna arrays, to support investigation into signalprocessing for interference alignment (IA), Section 3.2.6, and distributed MIMO, in


which the arrays have very large apertures, requiring coordination across multipleterminals.

One of the challenges to overcome in a system like this is the synchronisation oftransmitters. The design of the transmitted signal enables a self-synchronisationapproach at the receivers, but for multiple transmitter nodes, it is important that thetransmitters are well-synchronised so the receivers can clearly separate the character-istics of the different links. GPS signals are used to initialise triggering circuitry inboth transmitter units, which then maintain their timing using rubidium standards.The timing accuracy is ±50 ns when eight GPS satellites are in radio line-of-sight(LOS) [17]. This satellite visibility cannot be reliably achieved and maintained in thedowntown core, where most prior measurement campaigns were located.

Some preliminary experimentation led to the measurements being performed in thearea around the NRCan labs on Booth St. The building footprints in this area aresimilar to downtown Ottawa, but the buildings are not as tall, allowing adequate GPSsatellite visibility. Timing tests confirmed that these arrangements worked well.

One of the routes is shown in Figure 22. Both transmitters and one of the receiverswere mobile, and the other receiver was static [17]. The antenna elements werearranged linearly, with a one-wavelength separation, on the roofs of the mobile vansand static trailer, at 2–3 m above street level. The carrier frequency was 2 GHz.

Figure 22: Map of locations of two transmitters and two receivers, each with4-element antenna arrays, [17].


The spatial diversity achieved using antenna arrays is one of the key components insupporting high capacity communications (power is the other). There is a mathematicaldefinition of diversity, computed using the autocorrelation of the 4 × 4 matrix ofcomplex channel responses from the four elements at the transmitter to the fourelements at the receiver. For this size of array, the minimum diversity is 1, equivalentto having a single antenna element at each terminal, and the maximum possible is 4,which is unrealisable in practical configurations but is used as a theoretical constructin the academic literature. Empirical CDFs for the spatial diversity computed oneach of the four MIMO links on the measurement route of Figure 22 are shown inFigure 23. The diversity exceeds 2 for more than 70–80% of the time on all the links,which means there is good potential for exploiting spatial diversity to increase spectralefficiency.

Figure 23: CDFs of diversity on the four measured MIMO links, [17].

The measured data sets were also analysed to evaluate the benefits of distributedMIMO, by combining elements from both transmitter terminals and/or both receiverterminals. These analyses showed that the spatial diversities achieved for the dis-tributed configurations were similar to those for the single terminal configurations [17].

This is an important result because it indicates that the additional overhead fordistributed MIMO, such as coordination and message-passing between the terminals,provides limited-to-no gains. Further, to gain any small advantage of the spatialdiversity in the distributed MIMO case, a fairly sophisticated adaptive power normali-sation process is required, which increases the feedback overhead costs. This powernormalisation is not always possible, depending on the locations of the terminals,resulting in poorer performance for the distributed case. This was illustrated in [17]using an error rate analysis.


The cross-correlation characteristics of the measured channel data samples were alsoinvestigated. It was seen that, on average, the cross-correlation factors between signalvectors from different transmitter terminals to the same receiver were indistinguishablefrom those of noise [17]. This indicates that multi-node MIMO applications suchas interference alignment have good potential in complex environments such as thismeasurement location. It was noted that local conditions may exist where thecorrelation may be much higher, resulting in an inability to align the interferencesufficiently to achieve good throughput; however, as discussed in Section 3.2.6, across-layer approach such as time-slot adaptation may be appropriate to overcomethese physical effects.

This was the first known measurement of this type, providing simultaneous multi-linkMIMO channel characterisations. There is a large amount of insight to be extractedfrom this data set, if resources become available.

3.4.3 Air-to-ground measurements

Within the former TTCP C3I Technical Panel 6 (RF Communications), CRC was askedby the US Air Force Research Labs to collaborate on measuring air-to-ground channelcharacteristics. AFRL had been measuring radio performance on these links, butwithout channel modelling, they were not able to determine why the radio performedas it did.

Figure 24: AFRL UAV with CRC mini-sounder in cargo hold.

The measurement campaign took place near the end of the previous project, inAugust 2011, and early analysis results were published in [40], but the data analysisand channel modelling were not completed until the AC3E Project.


CRC developed a small, lightweight, low-powered two-channel MIMO sounding trans-mitter, which operated in conjunction with the MIMO channel sounding receiverterminal described in Section 3.4.1. The transmitter was mounted in AFRL’s UAV,Figure 24, which is constructed of balsa wood and fibreglass, and has a wingspan ofapproximately 2 m. Measurements were made at AFRL’s facility in Stockbridge, NY.

This air-to-ground scenario is quite different from the usual conditions envisioned forMIMO communications, which are typically highly complex, for example, the urbanarea considered in Section 3.4.2 and other measurement campaigns. The air-to-groundlink is line-of-sight (LOS), and the air platform moves very fast, particularly in thewindy conditions on the measurement days. This makes characterising the channelvery difficult, as the statistics are highly nonstationary and the signals experiencevery high, and rapidly changing, Doppler shifts.

The antenna elements on the air platform were mounted beneath the wings, andspaced by two wavelengths, at a carrier frequency of 915 MHz. The receiver terminalused an eight-element linear array with spacings of one-half wavelength. Measurementswere made with the receiver static and mobile, but the static measurements have beenmore extensively characterised and are the main source of insight into the channelproperties.

θy

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Figure 25: Illustration of plane and spherical waves at ground array [18].

Usually, MIMO channel models are derived assuming that incoming wavefronts areplanar, having been reflected from objects some distance from the array. Additionally,


in urban measurements such as those described in Section 3.4.1, the transmitter andreceiver arrays are at approximately the same heights, and most of the reflectingsurfaces are vertical, i.e., buildings, so there is little impact of elevation.

The key result from the air-to-ground channel modelling was the observation of near-field scattering, resulting from reflection of the incoming wavefronts with one or moreobjects close to the array, Figure 25. Modelling indicated the object was most likelythe roof of the measurement van. This is an interesting and useful observation, becauseit indicates that increases in spectral efficiency could be achieved even in these highlyLOS conditions, by exploiting the spatial diversity produced by reflections from boththe air and ground platforms. This effect could also be exploited in ground-only (orair-only) applications by judicious selection of the type and position of the antennason the platforms.

Sets of measurements obtained with the receiver inside and outside of the UAV’s flightcircuit were analysed to assess the utility of the UAV for range extension. It was seenin [18] that MIMO techniques could be applied in this scenario to increase the linkspectral efficiency, i.e., throughput, when the UAV is used as a relay.


4 Conclusions

The Assured Communications in Challenging and Contested Environments project,part of the Joint Force Development portfolio, demonstrated concepts for robustand reliable communications in remote and/or underserviced regions such as theArctic or in disaster recovery operations, and developed concepts, techniques anddemonstrations for flexible and adaptive access to spectrum in dynamic and congestedenvironments.

In the Arctic communications element, the Northern Access Node testbed was demon-strated using real-time links, showing the ability of the policy-based engine to selectappropriate connections based on user-specified requirements for quality of protectionand on the quality of service provided on each link. The development of the over-the-airtestbed illustrated various challenges in moving to real communications links, but theresulting demonstration was a valuable tool in showing the potential of a self-containednode to support communications in a remote or challenging environment, such as theArctic region or a disaster zone.

The objectives of the Spectrum Access element were to increase the efficacy androbustness of spectrum access through interference tolerance and adaptivity, and toenhance the spectral efficiency of networked communications in dynamic environments.New strategies for spectrum access were explored, evaluated and demonstrated, andsupporting concepts were developed.

The PBSA sub-element used a policy engine to make link decisions based on situationalawareness of the links’ quality as well as user requirements of signal quality and latency.This emulated both multiple mission-specific radio links connected to a NAN and asingle radio device with multiple available frequency channels. The demonstrationsuccessfully showed how real-time channel selection maintained connectivity whenlinks were degraded by delay or interference, and illustrated how lightly-manageddynamic spectrum access might be achieved.

In highly congested and dynamic spectrum environments, conventional spectrummanagement methods are inefficient and do not make the best use of the availablespectrum resource. Many users do not require interference-free conditions, anddo not occupy their assigned frequency 100% of the time. To take advantage ofthis, the concept of graceful frequency adaptation was investigated as an efficientand robust implementation of dynamic spectrum access. Users gradually changetheir carrier frequencies to maintain an acceptable performance in the presence ofinterference, eliminating the need for secondary radios and for high levels of controloverhead. Several aspects of this concept have been investigated, including partial


band interference tolerance and frequency adaptation algorithms. Spectrum labellingand altruism were considered as potential mechanisms to support spectrum accessbased on priority. It is clear that this approach to DSA has great potential, and thatthere is value in extending aspects of this work for proof-of-concept development,experimentation and demonstration.

Applying DSA techniques in mobile networks is particularly challenging becausethe nodes must coordinate frequency selection and changes amongst themselves, orroutes may fail, nodes may become isolated, or the network may become unstable.Preliminary work on a network coordination framework was undertaken, and a studyof MAC protocols was completed. This is an important area for further work beforeDSA can realistically be exploited in tactical networks.

While channel models are useful for developing and evaluating radio communicationconcepts, it has been observed repeatedly throughput this R&D program that thecharacteristics of real channels are not well-represented by those models. This is par-ticularly important for systems that exploit the spatial and/or temporal characteristicsof the radio propagation. In this project, channel measurements and analyses wereundertaken to investigate the spatial properties required to support advanced work innetworked communications, including interference alignment. The spatio-temporalproperties of urban environments were used to evaluate the requirements for waveformadaptation when radios change their frequencies across the UHF range.

To respond to increasing demands on the limited available spectrum for militarycommunications, it will be necessary to incorporate new strategies for spectrum accessinto the current spectrum regulatory, policy and management regime. The advancesmade within this Project show that both lightly-managed policy-based systems andautonomous spectrum access are worthwhile strategies for modernising spectrumaccess. Both these approaches use local spectrum situational awareness observations:it was shown that using a small number of simple, remote sensors to generate aspectrum occupancy map is not sufficiently reliable to support real-time spectrummanagement.

Due to resourcing limitations and restrictions, the work in the second element, Spec-trum Access, was not completed in its entirety, and there are aspects that requirefurther investigation. However, the advances in this project have developed severalnew concepts, and leave a strong foundation to support future S&T directions.


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[33] C. Squires, T. Willink, and B. Gagnon, “A flexible platform for MIMO channelcharacterization and system evaluation,” in WIRELESS 2003 – Proc. 15th Conf.on Wireless Commun., Calgary, Canada, Jul. 2003.

[34] T. Willink, “Cognitive radio techniques for assured communications: Final report,”Defence R&D Canada – Ottawa, Tech. Rep. TR 2010-004, Jan. 2010.

[35] I. F. Akyildiz, M. C. Vuran, and S. Mohanty, “A survey on spectrum managementin cognitive radio networks,” IEEE Commun. Mag., pp. 40–48, Apr. 2008.

[36] T. J. Willink, “Characteristics of urban vehicular mimo channels at differentfrequencies,” in 3rd Euro. Conf. Ant. and Propag. (EuCAP), Berlin, Germany,Mar. 2009.

[37] G. W. K. Colman and T. J. Willink, “Robustness of reduced feedback precodingin frame-based MIMO systems,” in Proc. IEEE Veh. Tech. Conf. (VTC),Sep. 2008.

[38] G. W. K. Colman and T. J. Willink, “Impact of MIMO pilot sequence length andframe length at different frequencies,” in Proc. IEEE Veh. Tech. Conf. (VTC),Sep. 2010.


[39] G. W. K. Colman and T. J. Willink, “Orthonormal diversity-multiplexing pre-coding in MIMO systems at finite SNR,” IEEE Commun. Lett., vol. 11, no. 8,pp. 650–652, Aug. 2007.

[40] C. Squires, T. J. Willink, and G. W. K. Colman, “Air-to-ground MIMO channelmeasurements,” in Wireless Communications 2012, Banff, AB, Jul. 2012.


Abbreviations and acronyms

AC3E Assured Communications in Challenging and Contested Environ-ments

AFRL Air Force Research LaboratoryARP applied research projectARQ automatic repeat requestBER bit error rateBPSK binary phase-shift keyingC3I Command, Control, Communications and Information SystemsCDF cumulative distribution functionCFD Chief Force DevelopmentCPM continuous phase modulationCRC Communications Research Centre CanadaDARPA Defence Advanced Research Projects AgencyDSA dynamic spectrum accessEIRP effective isotropic radiated powerEPLRS enhanced position location reporting systemGIG global information gridHF high frequencyIA interference alignmentISM industrial, scientific and medicalLOS line-of-sightLTE long-term evolutionMAC medium access controlMiDAS Military Digital Analysis SystemMIMO multi-input multi-outputNAN Northern Access NodeNF noise floorPBSA policy-based spectrum accessPBTM policy-based traffic managementPECC policy-enabled coalition communicationsPSD power spectral densityQoP quality of protectionQoS quality of serviceQPSK quaternary phase-shift keyingRF radio frequencySINR signal-to-noise-plus-interference ratioSNR signal-to-noise ratioTACOMS Tactical Communications StandardsTDMA time-division multiple access


TTCP The Technical Cooperation ProgramUAV unmanned aerial vehicleUHF ultra-high frequencyUSRP universal software radio peripheralVoIP voice over Internet protocol (IP)WNW wideband networking waveform


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Assured communications in challenging and contested environments

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Willink, T. J.

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June 2016

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security classification of the information in the paragraph (unless the document itself is unclassified) represented as (S), (C), or (U). It is

not necessary to include here abstracts in both official languages unless the text is bilingual.)

The Assured Communications in Challenging and Contested Environments (AC3E) Project com-

prised demonstrations of techniques for robust and reliable communications in remote and/or

under-serviced regions such as the Arctic, and the development of concepts and techniques

for flexible and adaptive spectrum access to provide robust networked communications in dy-

namic environments. Policy-based decision making combining situational awareness and user

requirements was the foundation for demonstrations of the Northern Access Node and real-time

spectrum access testbeds, which showed how robust channel access can be achieved with low

overhead and operator burden.

As modern waveforms are quite interference tolerant, conventional spectrum management ap-

proaches are unnecessarily rigorous and require expertise and effort. Advances in an autonomous,

interference-tolerant concept have been made, based on a graceful frequency adaptation strat-

egy. This has been found to be an efficient and robust basis for dynamic spectrum access in

mobile radio networks. Spatio-temporal channel measurements and analyses were undertaken to

support the investigations and to provide more realistic evaluations of adaptive capabilities and

requirements.

To respond to increasing demands on the limited available spectrum for military communications,

it will be necessary to incorporate new strategies for spectrum access into the current spectrum

regulatory, policy and management regime. The advances made within this Project show that

both lightly-managed policy-based systems and autonomous spectrum access are worthwhile

strategies for modernising spectrum access. Both these approaches use local spectrum situational

awareness observations: it was shown that using a small number of simple, remote sensors to

generate a spectrum occupancy map is not sufficiently reliable to support real-time spectrum

management.

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wireless communications; spectrum access; Arctic communications; radio propagation

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