performanceanalysisofmobileadhocunmannedaerialvehicle...

Hindawi Publishing CorporationInternational Journal of Aerospace EngineeringVolume 2010, Article ID 874586, 14 pagesdoi:10.1155/2010/874586

Research Article

Performance Analysis of Mobile Ad Hoc Unmanned Aerial VehicleCommunication Networks with Directional Antennas

Abdel Ilah Alshbatat1 and Liang Dong2

1 Department of Electrical Engineering, Tafila Technical University, Tafila 66110, Jordan2 Department of Electrical and Computer Engineering, Western Michigan University, Kalamazoo, MI 49008, USA

Correspondence should be addressed to Abdel Ilah Alshbatat, [email protected]

Received 8 April 2010; Revised 5 October 2010; Accepted 31 December 2010

Academic Editor: Hyochoong Bang

Copyright © 2010 A. I. Alshbatat and L. Dong. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Unmanned aerial vehicles (UAVs) have the potential of creating an ad hoc communication network in the air. Most UAVs usedin communication networks are equipped with wireless transceivers using omnidirectional antennas. In this paper, we consider acollection of UAVs that communicate through wireless links as a mobile ad-hoc network using directional antennas. The networkdesign goal is to maximize the throughput and minimize the end-to-end delay. In this respect, we propose a new medium accesscontrol protocol for a network of UAVs with directional antennas. We analyze the communication channel between the UAVs andthe effect of aircraft attitude on the network performance. Using the optimized network engineering tool (OPNET), we compareour protocol with the IEEE 802.11 protocol for omnidirectional antennas. The simulation results show performance improvementin end-to-end delay as well as throughput.

1. Introduction

Mobile ad hoc network (MANET) is a wireless network thatis formed by a collection of self-organizing mobile nodes.Each node communicates with its neighbors over a sharedwireless medium. Due to the lack of central management,nodes in MANET are designed to act as end systemsand routers for other nodes. The network is connecteddynamically and does not rely on any pre-existing networkinfrastructure. In MANET, nodes are free to move andhave the capability to deliver messages in a decentralizedmanner. A major challenge is how to route data packetsover such network that changes its structure dynamicallydue to member mobility, especially when the source and thedestination are out of transmission range [1].

Recently, there has been an increasing interest in employ-ing unmanned aerial vehicle (UAV) in wireless commu-nication networks [2]. UAV has been used in militaryapplications as well as civilian. It shows great advantagesin search and rescue, real-time surveillance, reconnaissanceoperations, traffic monitoring, and range extension [3]. Withthe advent of low-cost commercial off-the-shelf wireless

communication equipment embedded in the UAV platform,a swarm of UAVs can form a MANET in the air. UAV ad hoccommunication network is a new type of wireless networkfor communication among multiple UAVs. A collection ofautonomous UAVs dynamically form a temporary multihopradio network without the aid of any centralized station.

In UAV MANET communication environments, due tothe mobility of nodes, network topology may change rapidlyand unpredictably. As a result, nodes are expected to actcooperatively to establish network connection and to routedata packets over multiple hops for long distances [4]. Anetwork of low-altitude UAVs is usually complex comparedwith other types of wireless networks [5]. Wireless linkcreated by UAVs may alter in link quality over time dueto a number of factors such as Doppler effects, changes incommunication distance, and blocking of line-of-sight by theaircraft body. One challenge to use UAV as a node in MANETis the effect of aircraft attitude on the wireless link quality.The impact of aircraft attitude (pitch, roll, and yaw) on theMANET performance is significant. In particular, aircraftattitude affects the end-to-end delay and the throughput.These effects increase the retransmissions overhead and thus

2 International Journal of Aerospace Engineering

reduce the overall throughput and increase the end-to-enddelay. In order to reduce the impact of aircraft attitude,there is a need for designing a medium access control(MAC) protocol for such communication system that willcompensate for these effects.

Using miniature UAVs in wireless communication net-works may introduce a new challenge. The size of the light-weighted UAV is so small when compared with the size ofcommunication equipment required to transmit data overlong distances. One solution is to use high-gain directionalantennas. Directional antennas provide a number of advan-tages over omnidirectional antennas. As its name implies,directional antenna allows the signal to be transmitted in onedirection more efficiently, and at the same time cutting downthe interference by ignoring signals coming from places otherthan the desired one. Moreover, directional antenna is beingrecognized nowadays as a powerful method for increasingthe connectivity of ad hoc networks. The transmissionrange of directional antennas is usually larger than that ofomnidirectional antennas, resulting in the reduction in hopsbetween source and destination. Meanwhile, there is a needto develop efficient distributed algorithms to cope with theaircraft dynamics that affects the directivity of directionalantennas.

In this paper, we consider a collection of UAVs thatcommunicate through wireless links as a MANET usingdirectional antennas. All UAVs including miniature onesare equipped with unity gain omnidirectional antennasand directional antennas. Because of the size and powerlimitations, the use of the directional antennas in this paper isto increase the quality and reliability of the communicationlink without adding additional equipment, complexity, andpower consumption to the UAVs. Current MAC protocol(IEEE 802.11) that implements omnidirectional antennasmay not be suitable while using directional antennas.Therefore, there is a need for designing a new directionalMAC protocol that is capable for adapting any constraintsimposed by the UAV MANET. In that respect, to integrate thedirectional antenna successfully into UAV ad hoc networksand to realize its benefits within the MAC layer [6–10] andthe network layer, a new MAC protocol is introduced in thispaper so that the use of directional antenna will not becomea problem for the routing protocol but indeed will enhancethe performance of the network.

The remainder of this paper is organized as follows. InSection 2, we give a survey of current research regarding thedirectional MAC protocols and the concept of using UAV asa communication node in MANET. In Section 3, we describeour scheme which is called Adaptive Medium Access ControlProtocol for Unmanned Aerial Vehicle (AMAC UAV) anddiscuss its capability of adapting to the external parametersimposed by the UAV. In Section 4, we provide a statisticalmodel for the wireless channel between two UAVs andthe packet transmission time. In Section 5, we explainour implementation of the UAV communication networkin OPNET, and in Section 6, we present the simulationresults and provide a comparison with the MAC protocolfor omnidirectional antennas (IEEE 802.11). Finally, wesummarize the paper in Section 7.

2. Related Work

Recently, a large number of MAC schemes have beenproposed for MANETs that are equipped with directionalantennas. In general, most schemes that discussed the direc-tional antennas are focused on the modification of the MACprotocols [11–14]. Some researchers have suggested the useof switched beam antenna while others suggested the use ofadaptive antenna. Nasipuri et al. [15] proposed a directionalMAC protocol that utilizes switched beam antenna. Theyshowed that by using four directional antennas, the averagethroughput of the network could be improved up to threetimes over that of using omnidirectional antenna. Theyassumed that the gain of the directional antenna is equal tothe gain of the omnidirectional antenna. In their mechanism,the transmissions and receptions involve omnidirectionalantenna. The complete cycle starts by sending Request-To-Send (RTS) packet using the omnidirectional antenna.Receiver responds with a Clear-To-Send (CTS) packet alsousing the omnidirectional antenna. As soon as the transmit-ter receives the CTS packet, it estimates the angle of arrival(AOA) of this packet and transmits data using the directionalantenna.

In [7], the authors assumed (as in [15]) that the direc-tional gain equals the omnidirectional gain and proposedtwo MAC schemes. In the first scheme, RTS, acknowledg-ment (ACK) and data packets are sent directionally whileCTS packet is sent omnidirectionally. Other nodes that hearthe CTS should block the antenna on which it was received.In the second scheme, they proposed two types of RTS,Directional Request-To-Send (DRTS) and OmnidirectionalRequest-To-Send (ORTS) based on the following rule: (1)if none of the directional antennas of the node is blocked,the node will send ORTS. (2) Otherwise, the node willsend a DRTS provided that the desired directional antennais not blocked. The CTS, DATA, and ACK packets are thesame as in the first scheme. Compared with the scheme in[15], the node according to the MAC scheme in [7] maytransmit in directions that do not interfere with the ongoingtransmissions.

Other researchers [16–18] studied the performance ofMAC protocols with adaptive antenna array. Bao, et al. [18]developed a distributed Receiver-Oriented Multiple Access(ROMA) protocol for ad hoc networks in which all nodes areequipped with a multibeam adaptive antenna array. ROMAis capable of forming multiple beams and creating severalsimultaneous communication sessions. Another schemewas developed by the authors, called Neighbor-Tracking,which is used to schedule transmissions by each node in adistributed way.

A caching mechanism is a new technique which wasproposed to facilitate the operation of the MAC protocol fora node that is equipped with directional antenna [19]. A newcarrier sensing mechanism called Directional Virtual CarrierSensing (DVCS) was presented in [19]. This mechanismneeds information about AOA for each signal from thephysical layer. The authors have proposed the use of acaching mechanism to store information about angularlocation of neighboring nodes. Whenever the MAC layer

International Journal of Aerospace Engineering 3

receives a packet from the upper layer, it will look in thecache to determine whether it has the information aboutthe angular position of the destination node. If the angularposition of the destination node is known, the packet istransmitted using the directional antenna, otherwise it willbe sent using the omnidirectional antenna.

The authors in [20] designed another MAC protocolwhich uses multihop RTS to establish links between distantnodes; they called their protocol MMAC. In MMAC, whenany node receives RTS, it transmits CTS, DATA, and ACKover a single hop. In [19, 20], it was suggested to use theDirectional Network Allocation Vector (DNAV). DNAV issimilar to the NAV that is used in standard IEEE 802.11except that the DNAV stores the angle of arrival of theRTS packets in any given direction. For each packet tobe transmitted, the DNAV is consulted to see whether theangle of the packet to be transmitted is overlapped withany ongoing transmissions. If there are overlaps, the packettransmission is deferred; otherwise, the packet is transmitted.

In [21], the authors presented a scheme called utilizingdirectional antennas for ad hoc network (UDAAN). UDAANconsists of several new mechanisms such as neighbor discov-ery with beam forming, link characterization for directionalantennas, and proactive routing and forwarding. They haveshown that employing directional antennas improves systemperformance.

Orientation handoff is another name for the mechanismthat is created while integrating directional antenna withMAC protocol. This technique was invented to describethe process of switching from omnidirectional transmissionto directional transmission. In [22], the authors proposeda novel preventive link maintenance scheme based ondirectional antennas. They aimed to extend the life of thelink that is about to break. A warning is generated withina node when the received power is reduced below a certainthreshold. A node then switches to the process of creatinga directional antenna pattern to raise the received power sothat the link will not break.

Although directional antennas offer many benefits toMANET, they also present new problems. In [23], the authorproposed a new mechanism to solve different problems usingdirectional antenna, for instance, hidden terminal problemand exposed terminal problem. All these problems are solvedby building a MAC timing structure. In [24], the authorsanalyzed the performance of a wireless network usingdirectional antenna based on a different coding scheme. Inaddition, they analyzed the effect of direction estimationerror on the network performance. They derived the cumula-tive distribution function of the signal-to-interference-and-noise ratio (SINR) for a certain link and then analyzed theoutage probability of that link.

Locating and tracking nodes under mobility is a chal-lenge in ad hoc network. In most of the previous work, theauthors assumed that the transmitter knows the receiver’slocation. This assumption may not be true due to the factthat offering nodes’ positions may increase the overheadpackets, thus the MAC protocol should offer a mechanism tolocate and track node neighbors. Korakis et al. [25] proposedthe use of a circular RTS (CRTS) message to solve this

problem. In their protocol, RTS/CTS packets are transmittedon every beam. By doing so, they achieved a higher range butat the cost of high control overhead.

In [26], the authors proposed a polling-based MACprotocol that addresses the problem of neighbor discovery inthe use of directional antennas. The proposed MAC protocolis based on the polling strategy wherein a node polls itsneighbors periodically. Time is segmented into consecutiveframes and nodes are synchronized with each other. By thistechnique, each node is able to adjust its antenna weight inorder to track its neighbors.

Deafness problem is another challenge to ad hoc networkwith directional antennas. This problem is created as a resultof exchanging RTS/CTS directionally. In [27], the authorsproposed a new protocol called Toned MAC. Deafnessproblem was addressed by using subband tones. Tones aresinusoidal signals that do not contain information bits andthus do not require demodulation. They are only detectedthrough energy estimation and thus notify the neighbors ofa communicating node. The channel in a node that imple-ments this protocol must be divided in two subchannels: thedata channel and the control channel. The data channel isused for transmitting the four-way handshaking while thecontrol channel is used for transmitting the tone signal. Eachtone-frequency is identified by a unique code to assist nodesin determining the sender of a given tone.

In [28], the authors proposed a MAC protocol calledAdaptive Beam-Forming Carrier Sense Multiple Access/Col-lision Avoidance (ABF-CSMA/CA) by using smart antenna.This protocol, as others, employs the RTS/CTS/DATA/ACKaccess mechanism to manage node communications. In thisprotocol, training sequences are transmitted before apply-ing directional RTS and CTS packets. Training sequencesare mainly used to estimate the behavior of the wirelesschannel.

Integrating wireless equipment into a small UAV has beenstudied recently, especially in the context of MANET wherecommunication is required between nodes that would not beable to communicate because of line-of-site obstructions. In[29], the authors showed that by integrating small low-costcommercial off-the-shelf 802.11b equipment into a UAV, apowerful networking node can be created in the air. Theyalso showed that UAVs provided shorter routes that hadbetter throughput than a similar ground-based network. Tounderstand the performance of such a network, the authorsin [30] built a wireless network test bed using IEEE 802.11b.The test bed gave detailed data on network throughput, delay,range, and connectivity under different operating regimes.

In [31], the authors addressed the issue of configuring802.11a antennas in UAV-based networking and presenteda set of field experiments (test bed) to the wireless linkbetween UAVs and ground station. They measured the link-layer throughput based on various antenna orientations andcommunication distances. They concluded that both theUAV and the ground station should use omnidirectionaldipole antennas to get high throughput. In addition, theyshowed that the path loss in an airfield environment isroughly proportional to the square of the communicationdistance.


To improve the range and the reliability of ad hocground-based networks, the concept of using UAV as acommunication relay was presented in [32]. The authorsstudied the performance of the ad hoc ground network usingUAV as a relay node and the effects of UAVs’ positionsand velocities on Bit-Error-Rate (BER). In [33], the authorspresented the Load-Carry-And-Deliver (LCAD) networkingparadigm to relay messages between two distant groundnodes. This paradigm, LCAD, is designed for maximizingthe throughput of UAV-relaying networks by having a UAVload from a source ground node, carrying the data whileflying to the destination, and finally delivering the data toa destination ground node. They compared their paradigmagainst the conventional multihop and claimed that theproposed LCAD paradigm can be used to provide highthroughput between ground nodes.

In spite of these previous efforts, there are still problemsthat arise with the deployment of directional antennas forUAV communications and these are little work done thathandles multiple UAVs that form a MANET in the air. Noneof the previous approaches considers the effect of aircraftdynamics while implementing directional antennas. Aircraftdynamics is represented by three parameters: pitch, yaw,and roll. Any variation in these parameters could lead to anintermittent channel between the sender and the receiver andimpose a significant problem for the UAV communicationnetwork.

3. Adaptive MAC Protocol for Unmanned AerialVehicle (AMAC UAV)

UAVs are desired nowadays to extend the coverage ofcommunication networks. We propose the use of directionalantenna onboard UAV that can be steered in any direction. Incontrast to the traditional use of omnidirectional antenna,our approach provides low interference and robustness tothe wireless link and provides better network performancein end-to-end delay and throughput. In general, directionalantennas can be classified into two types: adaptive arrayand switched beam antenna. An adaptive array can beimplemented with an array of antennas, while a switchedbeam antenna can apply basic switching between predefinedbeams. Adaptive array can be more precise than switchedbeam antenna but with higher complexity in practice.

The performance of the UAV ad hoc network dependson several physical factors such as aircraft mobility andattitude. We assume that all UAVs are off the ground andfly at different altitudes. The distance between any two UAVswill not go beyond the transmission range of the directionalantenna. Two pieces of additional hardware are needed inour scheme for UAV localization: Global Positioning System(GPS) and Inertial Measurement Unit (IMU). When a packetarrives from the upper layer, the node requires the positionof the destination in order to steer the main lobe in theright direction. Control packet of RTS will be sent usingomnidirectional antenna. It includes the position of theaircraft and the duration of transmission. The destinationnode will respond with a CTS packet that has the sameinformation regarding itself. Each node that hears the CTS

or RTS should cache this information and updates its tablefor future use. The data packet will be sent using directionalantenna.

Figure 1 shows the flowchart of the proposed adaptiveMAC protocol for UAV ad hoc communication networkswith directional antennas. The implementation of thisscheme emphasizes the following issues.

(i) Every UAV is equipped with four antennas. Twoof these are directional. One directional antenna islocated on top of the UAV and marked primary, andthe other is located beneath the UAV and marked sec-ondary. The other two antennas are omnidirectional.If the UAV has no packet to send, it will listen to otherUAVs using one of the omnidirectional antennas. Ifthe UAV has packets to send, it has the choice to sendusing either one of the directional antennas or theomnidirectional antennas.

(ii) The locations of the UAVs are important factorsin the proposed scheme. With the proposed MACprotocol, each UAV frequently monitors the positionsof other UAVs and computes the effect of EulerAngles on the directional antenna.

(iii) The proposed MAC protocol frequently monitors theUAV distance, bit error rate, and retransmit counterso that it switches to omnidirectional antenna if thevalues exceed the limits.

(iv) In the case that there is no activity during a second,the UAV sends a heartbeat message using the omnidi-rectional antenna. This message contains the locationof the UAV. When it is received by another UAV, theUAV updates its table and responds with a similarheartbeat message.

(v) In the proposed scheme, each UAV is capable ofelectronically steering the antenna beam toward aspecific direction. Our modeling of the antenna isbased on a single beam that can target the boresightto any direction.

(vi) In the case that the aircraft changes its attitude, thepattern of the antenna will rotate with respect toits axis, resulting in fluctuations in antenna gain.These fluctuations affect the transmission range ofthe UAV communication. Therefore, the proposedMAC protocol compensates the antenna gain for anychanges by applying the same value to the targetlocation.

(vii) Switching time between primary and secondarydirectional antennas is assumed negligible.

According to the IEEE 802.11 MAC protocol, a packet isdiscarded after the retransmit counter exceeds 7. Meanwhile,as the number of retransmission attempts increases, thepossibility of delay increases. Based on the DistributionCoordination Function (DCF), a node senses the channelto determine whether it is idle or not. Sensing is donethrough physical and virtual mechanisms. If the mediumis sensed idle for a DCF inter-frame-space (DIFS) interval,


Back off

Packet to besent

Channelbusy

Compensator Compensator

Sendprimary

Sendsecondary

Send omni

Send omni

Alt 1 ≥ Alt 2

Update target information table

Ang 1(t-1)==

Ang 1(t)

Ang 1(t-1)==

Ang 1(t)

T = DIFS

R ≥ 5

Pck == control

Yes

Yes

Yes

No

No

No

No

Pass

Pass

Pass Pass

Targetinformation

D < Dmax

Yes

Yes Yes Yes

No

NoNo

FailFail

Fail

Figure 1: Flowchart of MAC protocol for UAV ad hoc communication network with directional antennas.

the node has the right to use the medium and startsending data. On the other hand, if the medium is busyor it becomes busy during the DIFS time interval, thetransmission will be deferred for a certain time until noother node occupies the medium. In such situation thebackoff timer is enabled. Our scheme follows the IEEE 802.11standard with some modification to the retransmit counter(retransmission threshold is set to be 5).

There are two methods for carrier sensing in the IEEE802.11 standard, physical carrier sensing and virtual carriersensing. Virtual sensing is done through the use of networkallocation vector (NAV). Two messages, RTS and CTS,precede the data transmission. These messages contain theduration for which the UAV should reserve the channel tocomplete the data transmission. On the other hand, any UAVthat overhears these messages should defer data transmissionfor this duration to avoid interference with other UAVs’transmission. In the proposed scheme, the RTS and CTScontain the location and orientation of the UAV. We use thedirectional network allocation vector (DNAV) mechanism[20] with some modification to adapt our scheme whileusing directional antennas for UAV communications. Our

DNAV is synchronized with the target information table thatis created through the handling of the control messages. Inaddition, the original NAV is also used in our scheme.

The procedure of the proposed MAC scheme is asfollows.

(1) To resolve the hidden terminal problem, the RTSand CTS are exchanged between the UAVs. Considerthe case when UAV number one attempts to send apacket to UAV number two. UAV number one willperform physical carrier sensing as in the IEEE 802.11standard. If the channel is idle, another sensing willbe done for NAV to see if the channel is reserved byanother UAV. Once the medium as well as the NAV isidle, UAV number one enters the backoff period fora certain time then RTS packet is sent through theomnidirectional antenna along with the parametersof UAV number one (location and orientation).

(2) UAV number one, as well as UAV number two, isequipped with GPS and IMU to provide the positionat high rates. Once UAV number one receives RTSfrom UAV Number One, it senses the channel for


short-inter-frame-space (SIFS) interval. If the chan-nel is free, it sends CTS along with the its parametersin response using the omnidirectional antenna andupdates the target information table as shown inTable 1. Other UAVs that also receive either RTS orCTS update their target information table as well asthe DNAV and NAV.

(3) Once UAV number one receives the CTS message, itupdates its target information table. Before initiatingtransmission of the data packets, the MAC checks thedistance between the two UAVs. If the distance is lessthan the transmission range of the omnidirectionalantenna (Dmax), the data are sent using the omni-directional antenna. Otherwise, the MAC checks theUAVs’ altitudes. If the altitude of UAV number oneis equal or less than that of UAV number one, dataare sent through the primary antenna (directionalantenna) along with UAV parameters. Antenna beamis steered to the direction of UAV number one.Otherwise, secondary antenna is used and is steeredto UAV number two.

(4) As soon as UAV number one receives the datasuccessfully and updates its target information table,ACK is sent using the omnidirectional antenna alongwith UAV parameters.

(5) For each data packet, the directional antenna issteered based on the destination location as well asthe source Euler Angles. To be more specific, considerUAV Number one’s attempt to send the second datapacket. The location of UAV number one is obtainedfrom the ACK. If UAV number one senses change inthe angles after receiving the target location, the MACcompensates for this change by applying the sameantenna gain value to the target location.

(6) As mentioned before, a packet is discarded after theretransmit counter exceeds 7. Since our goal is tominimize the end-to-end delay, the proposed schemewill switch the transmission from directional toomnidirectional if the retransmit counter reaches 5.

4. Performance Analysis

The performance of UAV ad hoc networks shall be measuredin terms of achievable throughput and end-to-end delay.Other features can also be investigated to evaluate therobustness of the proposed scheme, such as signal-to-noiseratio (SNR) and bit error rate (BER). In the following, wemodel the wireless channel between two UAVs statisticallyand investigate the packet transmission time.

4.1. Statistical Model for Wireless Channel between Two UAVs.To analyze the wireless communication link between twoUAVs using directional antennas, let us consider the examplein Figure 2. The transmitting UAV i is located at (Xi,Yi,Zi)(center) while the receiving UAV j at (Xj ,Yj ,Zj) (left lower).The aspect angle Φ defines the radiation of UAV i’s antennawith respect to UAV j. This angle consists of two parts, the

Table 1: Target information table.

TargetID

Latitude(Deg min

sec)

Longitude(Deg min

sec)

Altitude(Feet)

Direction

1 43 16 32 N 85 38 46 W 500 90

2 43 16 32 N 85 38 36 W 450 90

R

Pitch axis

ΦH

(Xi,Yi,Zi)

(Xi,Yi,Zi)Yaw axis

Line of sight

ΦV

Roll axis

Aspectangle Φ

Figure 2: Aspect angle Φ, the angle between the roll and the line ofsight.

horizontal aspect angle ΦH and the vertical aspect angle ΦV .ΦH is determined by the angle between the roll axis of UAV iand the line of sight (LOS) projected onto the yaw plane ofUAV i. ΦV is determined by the angle between the LOS andthe projection of the LOS onto the yaw plane of UAV i. Theabove angles depend on the locations of UAV i and UAV j aswell as the attitude of UAV i.

We assume that each UAV is equipped with a transceiver,directional antennas and omnidirectional antennas. Thewireless link between the two UAVs can be modeled withpath loss and fast fading. Path loss is basically caused bythe distance attenuation of the radiated power, and fadingis due to multipath effect of low altitude UAV propagation.Both cases are affected by the high mobility of the UAVssuch that there is rapid variation in the received signal power.Moreover, the fading level changes frequently. We assumethat there is a clear LOS between the UAVs. The averagepower of the received signal can be given using the Friis free-space transmission equation.

Pr = PtGtGr

(λ

4πR

)2

, (1)

where Pr represents power received by the receiving antennaand Pt power input to the transmitting antenna. Gt andGr are the antenna gain of the transmitting and receivingantennas, respectively. λ is the wavelength, R is the distancebetween the two UAVs, and 4πR/λ is the so-called free-spacepath loss. We assume that the bandwidth is narrow enoughthat the wavelength has a single value.

We set the receiving antenna gainGr(Φ′H ,Φ′

V ) = 1, whereΦ′

H and Φ′V are the aspect angels of the receiving UAV j


toward the transmitting UAV i. The received power can begiven as

Pr = PtGt(ΦH ,ΦV )(

λ

4πR

)2

. (2)

Taking logarithm of (2), we have

10 log10(Pr) = 10 log10(Pt) + 10 log10(Gt(ΦH ,ΦV ))

− 20 log10

(4πRλ

),

(3)

Pr(dBw) = Pt(dBw) + Gt(dBi)−Q0(dB), (4)

where Q0 represents the free-space path loss and is give by

Q0(dB) = 20 log10

(4πRλ

)

= 32.4 + 20 log10

(fMHz

)+ 20 log10(dkm),

(5)

where fMHz is the transmission frequency in MHz and dkm isthe distance between the two UAVs in kilometer.

The received signal in UAV communication experiencesrandom variation due to aircraft mobility, blocking andreflection of the fuselage, and terrain reflection in low-altitude flight. Such variation results in attenuation of thereceived signal power. Therefore, statistical models should beused to characterize the received signal in UAV communica-tion. In our case study, we consider a combined model withpath loss, shadowing, and fast fading effect. The total pathloss with signal attenuation (in dB) is given by

QT = Q0 + X + 20 log10(D), (6)

where X represents the log-normal shadowing effect. X (indB) is a zero-mean Gaussian random variable with standarddeviation σ (in dB). For large-scale path loss without the fastfading effect, the cumulative distribution function is given by

Pr(QT ≤ Qthreshold) =∫ a

−∞1

σ√

2πexp

(− X2

2σ2

)dX

= 1− 12

erfc(

a√2σ

),

(7)

where a = Qthreshold − Q0. Equation (7) can be used to findthe outage probability.

In equation (6), D is a random variable that representsthe received envelop of the fast fading signal. It followsRayleigh distribution or Rician distribution. The probabilitydensity function of the Rayleigh distribution is given by

p(D) = D

ρ2exp

(− D2

2ρ2

), D ≥ 0, (8)

where ρ2 is the time-average power of the received signal.When there is an unobstructed LOS between the transmit-ting and receiving UAVs, D follows the Rician distribution,which is given by

p(D) = D

ρ2exp

(−D2 + A2

2ρ2

)I0

(AD

ρ2

), D ≥ 0, (9)

Table 2: Medium access control header.

Framecontrol

Duration Address 1 Address 2 Address 3Sequencecontrol

(2 bytes) (2 bytes) (6 bytes) (6 bytes) (6 bytes) (2 bytes)

Table 3: Medium access control data unit.

MAC header Frame body FCS

(24 bytes) (2312 bytes) (4 bytes)

Table 4: ACK frame.

Framecontrol

Duration Receiver address FCS

(2 bytes) (2 bytes) (6 bytes) (4 bytes)

Table 5: Physical layer data frame.

Preamble Header MAC data unit

(144 bits) (48 bits) xxxx

where A denotes the peak amplitude of the dominant (LOS)signal component, and I0(·) is the zero-order modified Besselfunction of the first kind

I0(x) = 12π

∫ π

−πexp(−x sin τ)dτ. (10)

The ratio A2/(2ρ2) is called the Rician K factor. Thisparameter K measures the link quality and represents theratio of the power in the dominant (LOS) component tothe power in other non-light-of-sight (NLOS) multipathcomponents. As K increases, the link becomes clearer withless fading. The average received power in the Rician fadingcan be calculated as

Pr =∫∞

0D2p(D)dD = A2 + 2ρ2. (11)

SubstituteA2 = KPr/(K+1) and 2ρ2 = Pr/(K+1) in equation(9), we can write the Rician distribution in terms of K and Pr

as

p(D) = 2D(K + 1)Pr

exp

(−K − (K + 1)D2

Pr

)

·I0

(2D

√K(K + 1)

Pr

), D ≥ 0.

(12)

4.2. Packet Transmission Time. To evaluate communicationof the UAV ad hoc network, we analyze the performance ofthe MAC layer and the physical layer in terms of total timeneeded to transmit a packet. The time needed to transmit apacket is given by

Ttotal = DIFS + BackOffTime +(Data

(bytes

)

+28(bytes

))× 8DataRate(bit/sec)

+ SIFS

+ OverheadTime + ACKTime.

(13)


Table 6: Simulation parameters.

Parameter Value

Number of UAVs 4

Mobility Hexagon route

Simulation time 60 minutes

Data rate 11 Mbps

Area 2000 m × 2000 m

RTS threshold 256 bytes

Receive powerthreshold

−95 dBm

Transmit power 1 mW

Packet size 1024 bits

Packet interarrivaltime

Exponential

Destination IPaddress

Random

Radio propagationmodel

DSSS

DIFS and SIFS are used to ensure packet reception and avoidcollision between packets. The time specified for DIFS andSIFS differs based on the physical layer. In the following, weconsider direct-sequence spread spectrum (DSSS) parame-ters where SIFS = 10μs, TSlot = 20μs, DIFS = SIFS +2 × TSlot = 10 + 2 × 20 = 50μs, and BackOffTime =T Slot× Random(CW) = 20× 31 = 620μs.

The header of the MAC layer is shown in Table 2 and itconsists of 24 bytes. The whole data unit is shown in Table 3,where the frame control unit sequence (FCS) is attached toframe body and it has 4 bytes. Thus, 28 bytes compromisethe overhead in the MAC layer. The data length is limited to2312 bytes in 802.11b and 4095 bytes in 802.11g. ACK packetis short in size (14 bytes) and is shown in Table 4.

The overhead of the physical layer consists of a preambleand a header. Table 5 shows the physical layer data framein which a 144-bit preamble and a 48-bit header are addedto the frame. Therefore, with a 11-Mbps data rate, the timeneeded to transmit a 802.11b packet is

Ttotal = 50 + 620 + (2312 + 28)× 811

+ 10

+(144 + 48)

11+ 14× 8

11

= 2409.45μs.

(14)

5. Implementation of UAV Ad HocCommunication Network in OPNET

5.1. OPNET Modeler. The Optimized Network EngineeringTool (OPNET) modeler is considered a powerful soft-ware tool for network modeling and network performanceanalysis. The OPNET modeler is a discrete-event networksimulator that includes a set of detailed models for ad hocnetwork. It uses graphic user interfaces and allows users tocreate new models by either modifying existing models or

building new one. It uses finite state machine (FSM) modelin which a collection of states are linked together based onC code. Each state is divided into two parts: enter executiveand exit executive. Both parts specify a series of actions thata process implements when it occupies a state. The enterexecutive is executed as soon as the state is entered by theprocess while the exit executive is used in the unforced stateto implement a response to an interrupt.

5.2. Radio Transceiver Pipeline. In our simulations, wemodeled the wireless link between the transmitter andthe receiver with fourteen pipeline stages. These stages areprovided by the OPNET modeler and are connected betweenthe transmitter and the receiver as shown in Figure 3. Sixstages are associated with the radio transmitter and eightstages are associated with the radio receiver.

5.3. UAV Mobility Model. The movement of the UAV hasa significant influence on the performance of the network.Therefore, a lot of research has been devoted to builddifferent mobility models that are suitable for evaluatingthe performance of the UAV ad hoc network. A largenumber of mobility models were introduced. They havedifferent properties and each has its own advantages anddisadvantages. In our case study, the mobility model for UAVshould be close to real life. We model the mobility of the UAVwith six parameters (pitch, roll, yaw, latitude, longitude, andaltitude). Each UAV moves in a hexagon route as shown inFigure 4.

5.4. Modeling UAV Network Node with Two DirectionalAntennas and Two Omnidirectional Antennas. As shownin Figure 5, a UAV network node is modeled accordingto the Open Systems Interconnection (OSI) stack. Somelayers are omitted and some modifications are added to theoriginal modules. The UAV model consists of three mainparts: physical layer, data link layer, and upper layer. Thebottom part represents the physical layer. This part is slightlydifferent from the OPNET standard model. As shown inthe figure, the physical layer is composed of the transmittermodule, the receiver module, and the antenna module. InUAV transceiver modeling, we use three transmitters, onereceiver, and four antennas. One omnidirectional antennais connected to the receiver module and three antennas areconnected to the transmitter modules. One of the three is anomnidirectional antenna and the other two are directionalantennas. All of the above modules are responsible for thewireless communication between UAVs.

The middle part is the data link layer. This part isdivided into two modules. The first one is the originalMAC module (wireless lan mac) and the second one is theproposed module (UAV SUB MAC). The wireless lan macmodule implements the MAC protocol defined by theIEEE 802.11 standards. It is designed mainly to be usedwith omnidirectional antennas. Some modifications havebeen made to this module in order to link the directionalantennas with the radio transmitter modules and enablethis module to work as a two-mode module. The second


Transmissiondelay

Receiver antennaantennagain

Closure

Receiver group

Interferencenoise

Backgroundnoise

Receiver power

Transmittergain

Channel match

Signal to noiseratio

Bit-error- --rate

delay

Propagation

Error correction

Transmitter

Receiver

Error allocation

Figure 3: OPNET radio transceiver pipeline stages.

BC

D

FE

A

Figure 4: UAV mobility model in OPNET.

module implements the protocol described in Section 3, andit acts as an interface between the wireless lan mac and thelower layer. Both modules work jointly to serve the proposeddirectional MAC scheme.

The top part represents the upper layers. The upper layersare mainly composed of the modules such as ARP module,IP module, IP ENCAP module, TRAF SRC module, UDPmodule, DHCP module, MANET RTE MGR module, andCPU module. These modules generate data packets andimplement the Optimized Link State Routing (OLSR) proto-col. For example, TRAF SRC module performs the functionof generating raw packets. These packets are unformatted bitswhich are encapsulated as IP datagram by the IP ENCAPmodule. The IP module implements the IP protocol and theMANET RTE MGR module implements the OLSR protocoland manages the statistics for simulation runs.

As discussed earlier, the UAV SUB MAC module worksjointly with the wireless lan mac module. Figure 6 showsthe process model for the UAV SUB MAC. The process is

constructed by seven states. The function of each state isdescribed in the following.

(1) Init State: This state initializes the state variables andthe target information table.

(2) Idle State: This is the default state. The node entersthe idle state and waits for an incoming event. Theevent can be either self-interrupt or an incomingpacket from the wireless lan mac module. An incom-ing packet from the wireless lan mac will be checkedbased on its type, and control packet will be sentto the Omni State while data packet will be sent toTarget Table State. In addition, this state will read theparameters that affect the selection of antenna as wellas the MAC attribute values.

(3) Omni State: In this state, the incoming packet isforwarded to the omnidirectional antenna.

(4) Reset State: This state adds some delay to permitother modules to register themselves.

(5) Targe Table State: This state determines whether thepacket belongs to the primary state or the secondarystate based on the altitude of the UAV.

(6) Primary State: In this state, the target location isobtained in order to point the primary directionalantenna to that location. The UAV attitude isrecorded for each packet so that any change willtrigger the compensator.

(7) Secondary State: This state performs the same func-tionality as the primary state, but uses the secondarydirectional antenna.

As soon as a packet is received by the wireless lan macmodule from the upper layer, the wireless lan mac module


UAV SUB MAC

a 2a 1a 0 a 3

arp

ip

traf src

ip encap

dhcp

udp

CPU

manet rte mgr

wlan port tx 0 0 wlan port tx 0 1wlan port tx 0 2wlan port rx 0 0

Wireless lan mac

Figure 5: Modeling UAV network node in OPNET.

encapsulates the packet into a frame and sends it to theUAV SUB MAC module. In the OPNET simulator, eachnode has an ID. All nodes involved in the network registertheir IDs in a global array. The UAV SUB MAC module(Primary State and Secondary State) fetches the destinationnode ID from the received packet and retrieves its locationfrom the global array. Since all nodes are mobile, theproposed module fetches the target location for each packet,which includes longitude in degrees, latitude in degrees, andaltitude in meters. This information is then used by thePrimary State or the Secondary State to point the main lobeof the directional antenna to the target location.

6. OPNET Simulation Results

OPNET Modeler 14.5 is used for simulation of the UAVad hoc communication network. With the parametersshown in Table 6, we compare the network performanceof the proposed AMAC UAV protocol using directionalantennas with that of the IEEE 802.11 MAC protocol usingomnidirectional antennas. Four UAVs form a MANET ina simulated area of 2000 m × 2000 m. Both AMAC UAVand IEEE 802.11 MAC protocols operate at a data rate of11 Mbps. The simulation time is 60 minutes, and the UAVsare moving in the simulated area according to the hexagon-route mobility model with a constant speed of 40 m/sec. Thepacket size is set to be 1024 bits and the interarrival time isexponentially distributed. All UAV nodes in the network areconfigured to run the OLSR protocol. Moreover, each UAVis equipped with a transmitter, a receiver, two directionalantennas, and two omnidirectional antennas. Each UAV iscapable of electronically steering the antenna beam towarda desired direction. For each data packet to be transmitted,

the directional antenna is steered based on the destinationlocation as well as the source Euler Angles.

Figure 7 shows the performance comparison in end-to-end delay between the AMAC UAV protocol using direc-tional antenna and the IEEE 802.11 MAC protocol usingomnidirectional antenna. The end-to-end delay representsthe time interval from the instant that a packet is generatedby the source node to the instant that the packet is receivedby the destination node. This time interval increases whenthe packet passes through multiple hops between the sourceand the destination. The figure shows that the AMAC UAVprotocol results in small end-to-end delay compared with theIEEE 802.11 MAC protocol. This is because that the numberof hops is reduced when directional antennas are used withextended transmission range.

Figure 8 shows the performance comparison in through-put between the two protocols. The throughput of acommunication network is defined as the average rate ofsuccessful message delivery. In the figure, the maximumthroughput achieved by the IEEE 802.11 MAC protocol withomnidirectional antennas is less than 500 bps over the entiresimulation time. It decreases as the UAVs start to moveaway from each other. With the AMAC UAV protocol withdirectional antennas, as the UAVs move away from eachother, the throughput increases until reaching a saturationpoint. The result indicates that the network throughputcan be increased by using the AMAC UAV protocol withdirectional antennas. Figure 9 supports the above result. Itreveals that the maximum traffic received by a particularUAV node using the IEEE 802.11 MAC with omnidirectionalantenna is no more than 0.4 packet/sec. For the same amountof traffic sent, the node receives more packets when using theAMAC UAV protocol with directional antennas.


(Control stream)

Omni

IdleInit

105/1

(Self interrupt)

0/175

(Data stream)

26/0

23/0

Reset Primary

28/0

0/9

(Secondary)

Target table

rimary)/point ()

Secondary

29/0

Figure 6: OPNET process model of UAV SUB MAC.

0 500 1000 1500 2000 2500 3000 35000

1

2

3

4

5

6

7

8

×10−3

En

d-to

-En

dde

lay

(s)

AMAC UAVIEEE 802.11

Simulation time (s)

Figure 7: End-to-end delay of a MANET of 4 UAVs.

Figure 10 presents the simulation result regarding thereceive SNR. The receive SNR gives an indication about thequality of the received signal in which the higher the SNR thebetter the signal quality. As shown in the figure, the receivedSNR of the UAV ad hoc communication network employ-ing the AMAC UAV protocol with directional antennas isconsiderably higher than that using the IEEE 802.11 MACprotocol. Both protocols are modeled with the same pipelinesthat compute the background noise and the interferenceaffecting the incoming signal. In the simulation, the SNRresult of the AMAC UAV protocol is ideal, since it is assumedthat the steering of the directional antenna is precise and theinterference is kept to a minimum.

0 500 1000 1500 2000 2500 3000 35000

500

1000

1500

2000

2500

3000

3500

4000

Simulation time (s)

Th

rou

ghpu

t(bi

t/s)

AMAC UAVIEEE 802.11

Figure 8: Throughput of a MANET of 4 UAVs.

Figure 11 shows the comparison in received BER betweenthe UAV ad hoc communication networks employing the twoprotocols. The result is consistent with the previous resultin received SNR. As shown in the figure, the AMAC UAVprotocol gives less BER than the standard IEEE 802.11protocol. The proposed protocol gives a zero BER in the first1750 seconds, while the standard protocol gives more than3× 10−5 BER over the same period.

In another scenario, we simulate a MANET that isformed by twenty five UAVs. In a simulated area of 2000 m× 2000 m, the UAVs are initially deployed as shown inFigure 12. The simulation time is 10 minutes, and the UAVsare moving in the simulated area according to a random


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Traffi

cre

ceiv

ed(p

acke

t/s)

AMAC UAVIEEE 802.11

0 500 1000 1500 2000 2500 3000 3500

Simulation time (s)

Figure 9: Traffic received of a MANET of 4 UAVs.

0 500 1000 1500 2000 2500 3000 35000

50

100

150

200

250

Simulation time (s)

IEEE 802.11

SNR

(dB

)

AMAC UAV

Figure 10: Receive SNR of a MANET of 4 UAVs.

waypoint model with a zero pause time and a constant speedof 40 m/sec. All UAVs in the network are configured to runthe OLSR protocol. The packet size is set to be 1024 bits andthe interarrival time is exponentially distributed. The daterate is 11 Mbps and the transmit power level is 1 mW.

Figure 13 shows the performance comparison in end-to-end delay of this 25-node network between the AMAC UAVprotocol with directional antennas and the IEEE 802.11 MACprotocol with omnidirectional antennas. In general, there arethree factors that affect the end-to-end delay of a packet: timeto discover the route, buffering waiting time, and number ofhops of each path. Since the number of hops is reduced withthe AMAC UAV protocol, the end-to-end delay decreases.The end-to-end delay with both protocols is high at thebeginning of the simulation time. This reflects the fact that

0 500 1000 1500 2000 2500 3000 350010−9

10−8

10−7

10−6

10−5

10−4

Simulation time (s)

BE

R

AMAC UAVIEEE 802.11

Figure 11: Receive BER of a MANET of 4 UAVs.

Figure 12: Initial topology of a MANET of 25 UAVs.

the size of the control traffic is large before the selection ofthe Multi-Point Relaying (MPR) set.

7. Conclusion

A novel adaptive medium access control protocol is proposedfor UAV mobile ad hoc communication networks, whichis called AMAC UAV. Each UAV functions as a networknode and is equipped with two directional antennas and twoomnidirectional antennas. The UAV is able to receive packetusing the omnidirectional antenna and transmit packet usingeither the directional or the omnidirectional antenna. Thetransmitter can also choose from the two directional anten-nas mounted on top of and beneath the UAV and can steer


0

0.005

0.01

0.015

0.02

0.025

0 100 200 300 400 500 600

En

d-to

-En

dde

lay

(s)

Simulation time (s)

AMAC UAV

IEEE 802.11

Figure 13: End-to-end delay of a MANET of 25 UAVs.

the antenna beam toward the target. The OPNET Modeleris used to implement the proposed MAC protocol for theUAV ad hoc network. Each UAV network node is modeledand the antenna patterns are constructed by the antennapattern editor provided by OPNET. The data collected fromthe simulator are analyzed and compared with the samescenario but using standard IEEE 802.11 MAC protocolwith only omnidirectional antennas. It is revealed that theproposed AMAC UAV scheme with directional antennasprovides better performance for UAV ad hoc communicationnetworks in terms of end-to-end delay and throughput.

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