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Comparing Frequency Planning Against 1x3 and 1x1 Re-Use in RealFrequency Hopping Networks

U. Rehfuess, K. IvanovSiemens AG, Munich, Germany, {Ulrich.Rehfuess, Kolio.Ivanov}@icn.siemens.de

AbstractOn the one hand, the potential of radio link controloptions like frequency hopping, power control anddiscontinuous transmission for capacity increase inGSM mobile radio networks has been extensivelystudied by several authors using computer simula-tions in homogeneous hexagonal networks. Unfor-tunately, some idealistic assumptions on these net-work models have a substantial drawback on thepractical relevance of the simulation results. On theother hand, many field trials and regular networkoperation have proven very good results in terms ofboth network quality and capacity when applyingradio link options in tight frequency re-use. Butthere, systematic investigations are hardly feasible.Therefore, we present results of close-to-realitysimulations of FH networks showing that FH, PCand DTX can largely improve system capacity inreal non-homogeneous networks by as much as200%. We systematically investigate both advancedfrequency assignments at varying re-use and fre-quency assignments in cluster 1x3 and 1x1. Ourresults reveal some aspects contrasting widelyspread views on implementing FH in real networks.From our investigations we deduct recommenda-tions concerning the optimum approach of usingfrequency hopping, power control and discontinu-ous transmission in GSM networks.

1 IntroductionThe continually increasing number of subscribers inall GSM mobile radio networks is the driving forcefor mobile radio network engineers to design effec-tive capacity enhancement methods. The most at-tractive ones are those allowing for an increasednumber of radio carriers per base station (BS) bytightening the frequency re-use scheme. This iswhy radio link control options (RLO) like powercontrol (PC) and discontinuous transmission (DTX)for interference reduction and frequency hopping(FH) for interference averaging have been foreseenin the GSM standard [1].Both computer simulations and field experiencehave shown, that introducing FH allows for a lowermean carrier to interference ratio (CIR) for callswhile these calls experience equal or better frame

erasure rate (FER) than in the non hopping case.Based on speech quality, i.e. FER statistics, thehigh potential of RLO for capacity enhancementhas been demonstrated by several authors usingcomputer simulations of homogeneous hexagonalnetworks [2, 3, 4, 5, 6]. Typically, very tight re-useschemes down to 1x3 and 1x1 are proposed, sinceinterference diversity introduced by a large numberof hopping frequencies in tight re-use and usingthem only part-time, i.e. fractional load, reduces co-and adjacent channel collision probabilities.However, homogeneous hexagonal networks are anidealistic approximation of real world networks,since neither topography nor morphology effectsnor design options of the radio engineer related toantenna type and cell site can be modelled appro-priately in the homogenous approach. As a conse-quence, for real networks the potential of radio linkcontrol options up to now could be properly evalu-ated only by field trials. But even there, relevantquality measures like FER are hard to collect on astatistically relevant basis. An effective way tobridge the gap between idealistic simulation resultsand costly field trials in evaluating a variety of ca-pacity enhancement methods is to utilise the close-to-real-world information from conventional radionetwork planning tools in an integrated link andsystem level simulator. In Section 2 we outline thissimulation method and the way to interface thedynamic simulations with the output of a radionetwork planning tool. Section 3 deducts recom-mendations based on simulation results on typicalquestions arising when tight re-use and FH areplanned. In Section 4 we discuss achievable ca-pacities in automatically optimised frequency as-signments at medium tight re-use factors comparedto cluster assignments in 1x3 and 1x1. Section 5summarises our results and points out topics offurther investigation.

2 Real Network SimulatorIn conventional simulations, radio networks aretypically modelled as regularly distributed cells in ahomogeneous propagation environment leading toregular cell shapes like the well known clover leafstructure of a 3-sectored cell layout (cf. Fig. 1).

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Fig. 1: Homogeneous clover leaf cell layoutHowever, the Real Network simulator receives areal network configuration like BS co-ordinates,number of TRXs per cell and BS transmit powers,pathloss predictions and frequency allocation plansfrom a radio network planning tool (cf. Fig. 2).Based on this information, dynamic simulations canbe performed on irregularly positioned base sta-tions, non-homogeneous base station configura-tions, arbitrary frequency assignments and on close-to-reality propagation conditions [8].

Radio Network Planning

Real Network System Level Simulator

• network configuration• pathloss predictions• frequency assignment

Radio Network Model• Cell selection• MS positioning• implementation of FH,

PC, DTX, GSM frames• calculation of CIR burst

CIRburst

StatisticalRadio Link Model

• mapping of CIR burst ontoBER, FER, 1bRBER

Quality metrics, e.g. FERPlanning guidelinesParameter settings

Fig. 2: Real Network Simulator Overview The Real Network simulator interface maps thepathloss predictions from the radio network plan-ning tool onto a rectangular simulation area. Eachgrid point of the simulation area is uniquely as-signed to a certain cell referred to as a serving cell.The best server candidates are selected according totheir received level based on both the pathloss pre-dictions and BSs' transmit power plus a normallydistributed fading value in dB to model additionalshadowing. The effect of handover is taken intoaccount by a specified handover margin of e.g. 5dB [8]. In Fig. 3, a typical resulting cell layout is

shown. For the sake of simplicity of the figure,slow fading and handover margin effects are notdepicted resulting in fairly well shaped cell borders. If FH is applied, each BS uses all channels assignedin the planned frequency allocation within its hop-ping sequence. The BCCH frequency may be in-cluded or excluded in the hopping sequence. Forsufficient statistics, a large number of links ismonitored in a snapshot way, so called simulationcycles. Per simulation cycle, the Real Networksimulator randomly (Monte Carlo method) gener-ates one mobile station (MS) in one of the referencecells and MSs in all possibly interfering cells for allpossible interfering frequencies both on co- andadjacent channels. According to cell specific loadparameters, the interfering links are activated. Fur-thermore, a Poisson process is used to model theDTX speech activity, which can be adjusted byparameters. For both the reference BS-MS link andthe interfering BSs (DL) and MSs (UL), resp.,pathlosses are calculated. Based on the predictedpathloss from the network planning and the log-normal distributed slow fading, a fast fading valueis added per burst taking into account in a statisticalway the effects not modelled in the pure pathlosspredictions. PC is simulated as level based PC [5].Thus the Real Network simulator calculates CIR ona per burst basis considering effects of FH, PC andDTX. Since the BCCH can be assumed to be plannedconservatively to guarantee reliable signalling andmeasurement performance, only links on TCH fre-quencies in the reference cells are simulated. Nev-ertheless, for evaluation of frequency assignmentsderived in common band planning strategy andadjacent channel interference from BCCH to TCHchannels, the BCCH carriers are modelled as inter-ferers at constant maximum power level in all timeslots, i.e. without applying PC or DTX. The calculated CIR per burst is mapped onto a biterror rate (BER) per burst by a statistical radio linkmodel (SRLM)[2]. The BERs of eight consecutivehalf bursts are summed up to a BER per frame andmapped onto class1b residual BER and FER [2].The statistics of class1b residual BER and FER etc.are collected over all simulation cycles for eachreference cell. Hence, the QoS in terms of FER ordecoded BER of different frequency plans can becompared in one or more reference cells. The con-tribution of each reference cell to the overall resultcan be weighted either by the cell area or the car-ried traffic load.

3 Simulation ResultsThe following subsections shall demonstrate howdetailed insight into individual networks can be

Fig. 3: Typical resulting cell layout (without slowfading, HO margin = 0 dB)

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gained and how general rules for planning and im-plementing networks can be derived. In all figures,we use the well accepted method to find the appli-cable average system load that provides FER ≤ 2%for 90% of the calls.3.1 Common Band vs. Dedicated BandCommon band (CB) planning has been very popu-lar with many operators at sparse re-use, since itoffers very good BSIC performance which is vitalfor i.e. reliable handover. In simulations, CB hasproven to yield better voice quality than dedicatedband (DB) at sparse re-use. But CB limits capacitywhen re-use is tightened since co- and adjacentchannel interference from BCCH to TCH frequen-cies limit the benefits from fractional load in tightfrequency re-use, from DTX and most obviousfrom downlink PC, since the BCCH frequency hasto be constantly transmitted at maximum power atall times. Thus, DB planning is strongly recom-mended for maximising capacity since de-couplingof the physically different BCCH and TCH fre-quency properties allows for optimising both layersindependently and for fully exploiting interferencereduction measures on TCH channels. Well plannedsingle TCH pool solutions show superior perform-ance over a further split of the TCH band into mul-tiple re-use patterns as suggested in [7], since in thelatter case the solution space for advanced fre-quency assignment algorithms becomes limitedunnecessarily (cf. Fig. 4).

Dedicated BandCommon Band

5 hopping frequenciesPC on, DTX on

MRP 54.3%59.7%

71.8%

[%]

90%@FER≤2%

Fig. 4: Dedicated vs. common band vs. multiple re-use patterns at a mean re-use of 7

3.2 Cyclic Hopping vs. Random HoppingIn contrast to many textbook recommendation, CHcan be proven to perform superior to RH whenusing up to 10 hopping frequencies per cell. CHproduces inherently better frequency diversity thanRH, because with RH there is a rather high prob-ability to use a "bad" frequency more often withinthe interleaving depth than with CH, which makesisolated frame erasures quite probable. Besides itssuperior frequency diversity, CH may still yieldsufficient interference diversity. In the case where

the same physical interferer is faced on subsequentbursts, both C and I change their channel charac-teristics in an non-correlated way from burst toburst resulting in some “pseudo” interference diver-sity. Furthermore, real interference diversity can beplanned for in the network: Instead of using fre-quency groups, sophisticated frequency planningtools assign individual combinations of frequenciesto each cell thus generating different interferencerelations from burst to burst. Further real interfer-ence diversity in the CH case is generated by une-qual number of frequencies in re-use cells. There-fore, medium tight re-use assignments should beimplemented in CH mode (cf. Fig. 5).

55.4%

71.8% Cyclic FH Random FH

5 hopping frequenciesPC on, DTX on

[%]

90%@FER≤2%

Fig. 5: Cyclic vs. Random Frequency HoppingIn network configurations of 1x3 and 1x1, the latterconditions for CH are not fulfilled. Typically, thereare many hopping frequencies available leading to asatisfactory frequency diversity for RH. Thus, incluster 1x3 and 1x1, RH performs better than CH.3.3 Co- and Adjacent Channel Interference in

cluster 1x3 and 1x1In planned frequency assignments, the usage ofadjacent channels at sites typically is avoided by socalled co-site separation conditions in the assign-ment process. In cluster 1x3, all available TCHchannels are assigned to each site thus creating thepossibility of adjacent channel interference (ACI)between sectors. If all sectors at a site are synchro-nous in terms of their respective TDMA framenumbers, the proper assignment of mobile alloca-tion index offset (MAIO), which typically is used toavoid co-channel interference (CCI) within a cell,can be used to additionally prevent ACI betweensectors of a site [6]. In cluster 1x1, each sector ateach site uses all available TCH channels resultingin CCI and ACI between sectors. Again, synchroni-sation and MAIO assignment can be used to avoidboth CCI and ACI between sectors of that site. Inorder to investigate the gains of synchronisationand MAIO assignment, we calculate the achievablecapacity denoted in Erlang per site in a real net-work. This capacity per site is calculated by apply-

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ing the simulated maximum system load to theassigned TCH frequencies and adding those BCCHtimeslots not dedicated to signalling.

0

10

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40

50

60

70

80

1x3 1x1

Erl

/Site

CCI only, asynch

CCI + ACI, asynch

CCI + ACI, sync&MAIO

Fig. 6: Gains of synchronisation and MAIO as-signment in cluster 1x3 and 1x1 in a real network

Fig. 6 depicts the achievable capacities in a cluster1x3 and 1x1 applied to a real network. In the 1x3case, the network is limited by dominant CCI fromneighbour sites so that the addition of ACI hashardly any impact on the capacity. Consequently,the effort of synchronising the sectors and avoidingthe ACI between sectors by synchronisation andMAIO assignment does not provide large gains. Ina cluster 1x1 the threefold number of frequencies isavailable per sector compared to 1x3. This reducesthe collision probabilities between co-channel re-use cells significantly and allows for higher capac-ity when only CCI is regarded. When ACI is takeninto account, capacity is significantly reduced.Here, synchronisation and MAIO assignmentshows deliberate improvement of the network per-formance.

4 Maximising Capacity of FH networksAs outlined, capacity at good voice quality is themajor concern of network operators. Capacity canbe either limited by hard blocking, e.g. 2%, at lownumbers of TRXs or by soft blocking, i.e. violatingquality contraints such as the criterion of FER ≤ 2%in 90% of the calls. In the following charts wecompare the maximum achievable capacity denotedin Erlang per site in three sectored network con-figurations. We apply DTX, PC and use dedicatedband planning in all depicted configurations. Weuse an advanced automatic frequency assignmenttool explicitly minimising interference to generatefrequency plans with mean re-use factors down to 4and implement these plans in CH including theBCCH frequency. However, cluster 1x3 and 1x1are implemented in RH using synchronisation andMAIO assignment.As an example for a real network, we selected thenetwork of a major European city with its sur-roundings. In total, 273 cells were simulated. Per-formance was studied for the high capacity sites inthe city centre. A total of 43 carriers was available,resulting in 15 BCCH and 28 TCH frequencies. In

cluster 1x3 and 1x1, only 27 TCH channels wereassigned to separate BCCH and TCH layer by oneguard channel to avoid BCCH to TCH ACI at thesame site.

0

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30

40

50

60

70

80

21 14 9.3 7 4 1x3 1x1

Erl

/Site

CCI only

CCI + ACI

mean TCH re-use cluster

Fig. 7: Maximum capacity vs. TCH re-use in a realnetwork (15 BCCH, 28 TCHs)

Fig. 7 depicts the achievable capacities in that net-work. Configurations with sparse re-use are hardblocked at 2% (dashed line). When CCI only isconsidered, a clear maximum capacity is found at are-use of 7. When regarding the influence of ACIwe find that the highest capacity peak is the mostsensitive to ACI leading to a range of re-use from 9to 4 yielding similar capacities. This can be ex-plained by the fact, that at higher system loads theACI collision probability rises steeply making highloads more sensitive to ACI. Cluster 1x1 performswell in the CCI cases and even best of all whenACI is taken into account. However, Cluster 1x3shows rather poor performance due to the fact thatwe paint a map as depicted in Fig. 3 using onlythree colours thus violating the four colour theo-rem. This leads to poor mean CIR in many loca-tions. Due to rather high collision probabilities incluster 1x3 on co-channel, performance is inferior

0

20

40

60

80

100

120

140

21 14 9.3 7 4 1x3 1x1

Erl

/Site

CCI onlyCCI + ACI

mean TCH re-use cluster

Fig. 8: Maximum capacity vs. TCH re-use in a ho-mogenous “clover leaf” network ( 28 TCHs)

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to that of cluster 1x1 with the threefold number offrequencies. However, in a homogeneous networkcluster 1x3 performs significantly better than clus-ter 1x1 (cf. Fig. 8), because here three colours aresufficient to colour the idealistic clover leaf struc-ture (cf. Fig. 1). Still, a re-use of four performssuperior due to better overall CIR guaranteed by thefrequency assignment. Since the homogenous net-work structure provides better overall CIR, all con-figurations suffer less soft blocking leading tohigher capacities than in the real network case.Comparisons over various simulated networks yieldsimilar results. When both CCI and ACI are con-sidered, optimised frequency assignments over arange of medium tight re-use yield good perform-ance trading better CIR at sparser re-use againsthigher gains from FH and fractional loading intighter re-use. Cluster 1x1 with synchronous sectorsand proper MAIO assignment shows similar per-formance as the optimised assignments at reducedplanning effort. Cluster 1x1 is of particular interestwhere few TCH spectrum is available. Cluster 1x3is only advantageous where real networks perfectlymatch the ideal clover leaf structure.

5 ConclusionsWe presented several simulation results from aclose-to-reality approach taking into account thevariety of non-homogeneities in real environments.It has been shown that also in real networks FH, PCand DTX yield large capacity gains. Two distinctways have been shown to achieve these gains: Ei-ther advanced frequency assignment shall be usedat medium tight re-use to optimise the overall CIR.In this case, the rather low number of hopping fre-quencies shall be used in cyclic FH mode includingthe BCCH frequency to maximise frequency diver-sity gains. For good performance, good networkmodelling in terms of pathloss predictions and us-age of advanced frequency assignment algorithmspay in extra capacity. Or the frequency planningeffort can be reduced for TCH frequencies by usinga cluster 1x1 implemented in random FH to maxi-mise interference diversity gains. Here, synchro-nous sectors per site with proper MAIO assign-ments have proven to be advantageous. In non-homogeneous networks cluster 1x3 has been shownto be a bad compromise between these two ways,because the 4 colour theorem is violated leading topoor CIR in many areas of the network withoutproviding sufficient interference diversity. For realnetworks, the decision between the two suggestedways depends on the grade of homogeneity of theparticular network configuration in terms of terraincharacteristics, on/off-grid site positioning etc. andthe available spectrum.

Further simulator development is heading towardsdynamic simulations, i.e. links are generated anddiscarded randomly in Poisson processes andmonitored during their active phase while the MSsmove through the network. Besides more realisticmodelling of subscriber behaviour, this will allowfor analysing handover and directed retry.AcknowledgementsThe authors wish to thank the colleagues inSiemens AG from the network planning and net-work engineering departments for corporation andfruitful discussions. Furthermore, the authors grate-fully acknowledge the contributions of U. Schwark,W. Rixner and H. Yu during their diploma theses atSiemens Mobile Networks division. Also theauthors appreciated very much the great support ofthe Mobile World architects H. Winkler and G.Spring of Siemens in Vienna.References[1] M. Mouly, M.-B. Pautet: ”The GSM System

for Mobile Communications”, Cell & Sys,1992.

[2] K. Ivanov, G. Spring, N. Metzner, P. Jung:”Frequency Hopping - Spectral Capacity En-hancement of Cellular Networks”, in Pro-ceedings of the 4th IEEE ISSSTA Conference,pp. 1267-1272, Mainz, Sep. 1996.

[3] C. Carneheim, S.-O. Jonsson, M. Ljungberg,M. Madfors, J. Näslund: ”FH-GSM FrequencyHopping GSM”, Proc. 44th IEEE Conf. Veh.Technol., pp. 1155-1159, 1994.

[4] H. Olofsson, J. Näslund, B. Ritzen and J.Sköld: ”Interference diversity as means for in-creased capacity in GSM”, in Proc. 1st Euro-pean Personal and Mobile CommunicationsConference, 1995, pp. 97-102.

[5] J. F. Whitehead: ”Signal Level Based PowerControl for Co-Channel Interference Manage-ment”, Proceedings 43th IEEE VehicularTechnology Conference, 1993, pp. 499 - 502.

[6] T. T. Nielsen et. al.: ”Slow Frequency Hop-ping Solutions for GSM Networks of SmallBandwidth”, Proc. 48th IEEE Vehicular Tech-nology Conference, 1998, pp. 1321-1325.

[7] F. Kronestedt and M. Frodigh: ”FrequencyPlanning Strategies for Frequency Hopping”,Proc. 47th IEEE Vehicular Technology Confer-ence, 1997.

[8] U. Rehfuess, K. Ivanov and C. Lueders: ”ANovel Approach of Interfacing Link and Sys-tem Level Simulations with Radio NetworkPlanning”, Proc. Globecom 1998, pp. 1503-1508.