Local Interference Coordination in Cellular OFDMA NetworksMarc C. NeckerInstitute of Communication Networks and Computer Engineering, University of StuttgartPfaffenwaldring 47, D-70569 Stuttgart, GermanyEmail: marc.necker@ikr.uni-stuttgart.de

Abstract

The currently emerging 802.16e (WiMax) and 3GPP Long Term Evolution (LTE) cellular systems are based onOrthogonal Frequency Division Multiple Access (OFDMA). AsOFDMA is basically a combination of FDM andTDM, it suffers from heavy inter-cell interference if neighboring basestations use the same frequency range.However, it is desirable to reuse the complete available frequency spectrum in every cell in order to maximizethe resource utilization. One possible approach to solve this conflict is the application of beamforming antennas incombination with interference coordination mechanisms between basestations. Starting from a global interferencecoordination scheme with full system knowledge, we first investigate how spatially limited interference coordinationaffects the system performance. Subsequently, we study several realizable interference coordination schemes andshow that a locally implementable scheme can almost match the performance of the global scheme with respect tothe sector throughput.

1 IntroductionSeveral emerging standards for cellular broadband net-works, such as 802.16e (WiMax) or the future 3GPPLong Term Evolution (LTE) are based on OrthogonalFrequency Division Multiple Access (OFDMA). InOFDMA, users are multiplexed in time and frequencybased on an underlying OFDM system. A major prob-lem in these systems is the inter-cell interference thatneighboring cells cause when using the same frequencyband. Classical FDM/TDM systems like GSM mitigateinter-cellular interference by avoiding the reuse of thesame set of frequencies in neighboring cells by em-ploying a frequency reuse pattern. Another possibilityis to use beamforming antennas, which focus theirtransmission or reception in the direction of a particularterminal. This minimizes the interference to terminalsin other directions. Finally, the transmissions of neigh-boring base-stations can further be coordinated, thusalmost completely eliminating inter-cell interference[1]. This is referred to as interference coordination(IFCO).

IFCO is gaining more and more attention in thecourse of 3GPP LTE and 802.16e, as it seems themost promising approach to solve the problem of inter-cell interference in OFDMA-systems while achievinga high spectral efficiency at the same time. Besides asolid network and protocol architecture to allow therealization of IFCO, intelligent algorithms to coordinatethe transmissions to different terminals are needed.

In [1], we investigated a global interference coordi-nation scheme with beamforming antennas and full sys-tem knowledge in a dynamic 802.16e-system. Despitethe fact that such a global scheme is not realizable, itprovides an important reference for future distributedsolutions. Based on the scheme presented in [1], we

study in this paper the impact of limited coordinationbetween basestations as it would be the case in anactual system. We subsequently introduce several IFCOalgorithms which are implementable locally within abasestation and compare their performance to the globalscheme. We finally propose a local algorithm with al-most the same spectral efficiency as the global scheme.

This paper is structured as follows. In section 2, theinvestigated 802.16e-system is introduced. Section 3details the considered IFCO algorithms, and section 4presents the performance evaluation. Finally, section 5concludes the paper.

2 System model

2.1 Overview of transmission systemWe consider an 802.16e-system [2] with a total avail-able system bandwidth of10 MHz and a MAC-frame-length of5 ms. This results in a total numberof 49 OFDM-symbols per MAC-frame and 768 datasubcarriers per OFDM-symbol. Each MAC-frame issubdivided into an uplink and a downlink subframe.Both subframes are further divided into zones, allowingfor different operational modes. In this paper, we focuson the Adaptive Modulation and Coding (AMC) zonein the downlink subframe. In particular, we consider theAMC 2x3 mode, which defines subchannels of 16 datasubcarriers by 3 OFDM-symbols. This is illustrated inthe left part of Fig. 1. A subchannel corresponds to theresource assignment granularity for a particular mobileterminal. The AMC zone can therefore be abstracted bythe two-dimensional resource field shown in the rightpart of Fig. 1.

We assume the AMC zone to consist of 9 OFDM-symbols, corresponding to a total number of48 · 3

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available subchannels. Adaptive Modulation and Cod-ing was applied ranging from QPSK 1/2 up to 64QAM3/4. This results in a theoretical maximum raw datarate of about6.2 Mbps within the AMC zone. The burstprofile management is based on the exponential averageof the SINR conditions of the terminal’s previous datareceptions.

2.2 Simulation modelWe consider a hexagonal cell layout comprising 19basestations at a distance ofdBS = 1400 m with120

◦ cell sectors as shown in Fig. 2. The scenariois simulated with wrap-around, making all cells equalwith no distinct center cell. Throughout our paper, weevaluate the shadedobservation areawhen investigat-ing the cell coverage, and the average of all cell sectorswhen considering throughput metrics. All cells wereassumed to be synchronized on a frame level. Eachsector containsN = 9 fully mobile terminals movingat a velocity of 30 km/h, which are restricted to theirrespective cell sector in order to avoid handovers (see[1] for more details).

Every basestation has 3 transceivers, each servingone cell sector. The transceivers are equipped withlinear array beamforming antennas with 4 elementsand gain patterns according to [1]. They can be steeredtowards each terminal with an accuracy of1

◦ degree,and all terminals can be tracked ideally.

3 Interference Coordination andResource Assignment

3.1 General procedureIn order to realize the coordination of cell sectors, wedivide the scheduling process into two steps, which areperformed for each MAC frame:

1) Interference coordination:In this step, the re-sources available for each mobile terminal arerestricted according to a certain algorithm. Bydoing so, it can be avoided that certain mobileterminals in different cells are served by using

the same set of resources.2) Resource assignment:In this second step, a

scheduler assigns resources to the different ter-minals, while taking into account the constraintsof the previous step. This is detailed in section3.4.

Note that it depends on the respective interferencecoordination mechanism whether a distributed or even alocal implementation of these two steps may be feasibleor not.

In the following, we consider two interference co-ordination algorithms, including several variants andcombinations thereof. Section 3.2 summarizes theglobal interference coordination scheme from [1]. Sec-tion 3.3 introduces Fractional Frequency Reuse (FFR)and the considered variants. Finally, section 3.4 detailsthe resource assignment procedure.

3.2 Interference Coordination with Inter-ference Graph

This scheme from [1] is based on an interferencegraph whose nodes represent the mobile terminals, andwhose edges represent critical interference relations in-between the terminals. Terminals which are connectedmust not be served using the same set of resources. Foreach terminal, the interference from basestations withina certain diameterdic of the serving basestation is cal-culated. Afterwards, the largest interferers are blockedfrom using the same set of resources by establishinga relation in the interference graph. This is done suchthat a desired minimum SIRDS is achieved for eachterminal. For a detailed description, please refer to [1].

The coordination diameterdic denotes the maximumdistance which two basestations may have in orderto still be coordinated. The larger the coordinationdiameter, the more challenging is an implementationin a real system. In [1],dic was infinite, which impliesa global interference coordination with an omniscientdevice capable of instantly acquiring the system state

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Fig. 2: Hexagonal cell layout with wrap-around

and assigning the resources on a per-frame basis. Thisis an ideal solution, which is not feasible in an actualsystem, but it provides some important performancemetrics for the comparison of realizable algorithms.

Limiting dic to the distancedBS between two bases-tations restricts the coordination to neighboring bases-tations. This coordination with a diameter of one tier(one-tier coordination) requires signaling only betweenneighboring basestations giving way to a possible dis-tributed realization of the interference coordination.Further decreasingdic leads to a coordination onlyamong the sectors of the same basestation (zero-tiercoordination). Such a scheme was proposed in [3]. Itcan be implemented locally within a basestation anddoes not need any signaling among basestations.

3.3 Fractional Frequency Reuse (FFR)FFR is a well-known concept to mitigate inter-cellinterference without the need for global coordination.It is based on the idea of applying a frequency reuseof one in areas close to the basestation, and a higherreuse in areas closer to the cell border. This idea wasfirst proposed for GSM networks (see for example [4])and has been adopted in the WiMAX forum [5], butalso in the course of the 3GPP Long Term Evolution(LTE) standardization, e.g., in [6] and [7], where thefocus lies on practically implementable algorithms.

Several variations of such a scheme are possible.In [3], the reuse 1 and reuse 3 areas are on disjointfrequency bands, while [6] and [7] use the full set ofavailable resources in the reuse 1 areas and one thirdof the same resources in the reuse 3 areas. Variationsare also possible with respect to the transmit powerlevel in each of the areas. In [6], the reuse 1 areas arecovered with a reduced power level, while in [7] thetransmit power of interfering base stations is reduced.In this paper, we will use the full set of resources forthe reuse 1 areas and one third of the same resourcesfor the mobiles in the reuse 3 areas. The power will notbe controlled as part of the interference coordination,but in the course of the burst profile management.

The assignment of mobile terminals to reuse 1 orreuse 3 areas can be done based on the distancedMT

of a mobile terminal from the basestation [3], or onthe present SINR situation. In this paper, we considerboth possibilities. For the distance-based assignment,a distance ratiod13 = 2dMT/dBS is introduced. IfdMT < d13, the mobile terminal is considered to be inthe frequency reuse 1 area, otherwise it is consideredto be in the reuse 3 area.

The SINR-based assignment can be done based onmeasurements in the mobile terminal. These can bebased on the measurement of pilots from the servingand the interfering basestations, or on measurements ofrecently received data frames. The measurements needto be fed back to the basestation, which is also requiredfor other purposes, such as burst profile selection. Inthe following, we will only consider measurements onactually received data frames. To take into account the

high variability of the instantaneous SINR, the decisionregarding the reuse 1 or reuse 3 area is based on ahysteresis. This is done by introducing an upper SINRthresholdthup and a lower SINR thresholdthlow, asillustrated in Fig. 3. Instead of the instantaneous SINR,an exponential average of the previously experiencedSINR-values of each mobile terminal is used, whichreflects the averaged SINR conditions the mobile ter-minal is currently experiencing.

FFR can be combined with an additional interferencecoordination algorithm. In [3], it was proposed tocoordinate the transmissions within the sectors of onebasestation on top of the distance-based FFR scheme,while the coordination algorithm was not described.In the following, we propose to combine the distance-and SINR-based FFR with the interference graph basedcoordination scheme described in the previous section.We will limit the interference graph based algorithm tojust local coordination in-between sectors of the samebasestation (zero-tier coordination), in order to preservethe possibility of a local implementation of the FFRscheme. We will show that FFR in combination withthe additional local interference coordination greatlyoutperforms a pure FFR scheme with no coordination.

Note that in contrast to classical Dynamic ChannelAssignment (DCA) schemes, in particular AutonomousReuse Partitioning (ARP) (see for example [8] for agood overview), the here investigated FFR schemes aremuch more dynamic on a per-frame basis and addition-ally utilize the benefits of beamforming antennas andlocal interference coordination.

3.4 Resource Assignment

In each cell sector, a Random scheduler is used, whichassigns the highest scheduling priority to each of theN terminals in the sector at least once within a periodof N MAC-frames. For each MAC frame, the resourceassignment process begins by randomly selecting a cellsector and assigning a rectangle of3× 12 subchannelsto the highest priority terminalmk. If an interferencegraph is used for interference coordination, the assignedresources are blocked for all other terminals connectedto mk in the interference graph. Afterwards, anothercell sector is randomly selected and the highest pri-ority terminal is assigned resources, obeying possibleresource blockings. Once all sectors have been visited,the whole procedure is repeated with the second highestpriority terminals, and so on.

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4 Performance Evaluation

4.1 Scenario and simulation parameters

The system model was implemented as a frame-levelsimulator using the event-driven simulation libraryIKR SimLib [9]. The path loss was modeled accordingto [10], terrain category B. Slow fading was consideredusing log-normal shadowing with standard deviation8 dB. Frame errors were modeled based on BLER-curves obtained from physical layer simulations. Thesimulation model comprised all relevant protocols,such as fragmentation, ARQ and HARQ with chasecombining. All results were obtained for the downlinkdirection with greedy traffic sources. Throughputmeasurements were done on the IP-layer, capturing alleffects of SINR-variations and retransmissions. Thisalso captures the overhead of MAC protocol headersand padding of the 64-Byte ARQ blocks when packingthem into bursts.

4.2 Interference coordination based on in-terference graph

In the following, we consider the influence of the co-ordination diameter as introduced in section 3.2, whichis a first step towards a distributed implementation.As a reference, Fig. 4 shows the average achievablethroughput over the observation area as defined inFig. 2 for a classical frequency reuse 3 system withbeamforming antennas. The mean sector throughput isabout 890 kBit/s, corresponding to a spectral efficiencyof almost0.5 Bit/Hz/s1. In this scenario, the obtainedthroughput in the center of the cell is about 2—3 timeshigher than in the cell border areas.

The total sector throughput for the interferencecoordinated Reuse 1 system is shown in Fig. 5, fordifferent diametersdic. As we increaseDS , the SIRconditions improve, while on the other hand the re-source utilization decreases due to an increased numberof interference graph conflicts. This leads to a tradeoffand a maximum of the observed total sector throughputfor a particularDS . This effect was studied in [1].

1This is an increase of about 50% over a reuse 3 system withsector antennas.

With respect to the coordination diameter, the totalsector throughput decreases asdic is decreased. Forsmallerdic, it is more difficult to control the interfer-ence situation in the border areas of the cell sectors,and it is no longer possible to achieve uniform SIRaverages in the area as those observed in [1] withglobal interference coordination. Consequently, largervalues ofDS are required to compensate this effect andachieve the maximum sector throughput. In all cases,the achieved sector throughput is higher than in thereuse 3 system.

Besides the total sector throughput, fairness is animportant issue. In particular, terminals which are faraway from the basestation should still receive an ac-ceptable service. The 5% throughput quantile is a goodindication for the achievable throughput in the cellborder areas [11]. It is captured by measuring theaverage short-term throughput of each terminal within4-second periods and calculating the quantile over allmeasurements. The 5% quantile is shown in Fig. 6depending on the total sector throughput. The measure-ment points are spaced 5 dB apart and correspond to thevalues ofDS in Fig. 5. For a zero-tier coordination, themaximum sector throughput automatically delivers thebest cell edge performance. For a larger coordinationdiameter the cell border performance can be tradedoff against the aggregate throughput. This is particularthe case for the one-tier coordination. In contrast, thetwo-tier coordination has even more control over theSIR in the cell border areas and achieves an almostmaximum throughput quantile and maximum aggregatethroughput at the same time. Note that the throughputquantile decreases as the minimum desired SIRDS

increases, since more conflicts in the interference graphare introduced, especially for mobile terminals in thecell border areas.

Figure 7 and 8 give even more insight by plottingthe throughput in the observation area for the one-tierand the zero-tier coordinated system. The throughputimprovement is mainly observed in the inner portion ofthe cell area, especially when comparing the results tothe reuse 3 system in Fig. 4. The graphs also reveal thecell border areas where the throughput is particularlylow. The throughput in the border areas could be

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improved by moving to a two-tier coordination, or bysacrificing aggregate sector throughput.

Note that a coordination of only neighboring bases-tations achieves an almost as good performance as acoordination with a larger coordination diameter withrespect to the aggregate throughput. Even the zero-tiercoordination, which takes place within a basestationand therefore is well-feasible, achieves a performancegain of approximately 30% over the reuse 3 system.However, the zero-tier coordinated Reuse 1 systemsuffers from degradation in the cell border areas andcannot match the aggregate performance of the systemswith a larger coordination diameter. One approach tosolve this problem while still avoiding coordination in-between basestations is the usage of FFR.

4.3 Distance-based FFR

The main system parameter in the distance-based FFRscheme is the distance ratiod13. If d13 is increased,the cell area where a reuse of 3 is enforced becomessmaller and the utilization of resources increases. Atthe same time, the SIR decreases. Naturally, this willlead to a tradeoff. This becomes obvious in Figure 10,which shows the total sector throughput depending ond13 for different values ofDS . A desired SIRDS of20 dB delivers the best results. This is in line with theresults of the pure 0-tier coordination in Fig. 5. Withrespect to the distance ratiod13, a value of about0.6

delivers the best results, which nicely fits the resultsof [3].

Figure 11 plots the 5% throughput quantile over thetotal sector throughput forDS = 20 dB. With respectto both the quantile and the total throughput, theperformance of the interference graph based schemewith inter-cellular coordination cannot be met. Theperformance is rather comparable to the previouslyinvestigated zero-tier coordination scheme, where theadditional FFR now allows to trade off the throughputquantile and the aggregate sector throughput. Fromthe chart we can see that the aggregate throughput canbe pushed to an almost as high throughput as in theglobally coordinated system while sacrificing 50-70%of the cell border performance.

The area throughput in Fig. 9 reveals a sharp edgeat the given distance ratio, where the throughput dropsby a factor of 4—5. This is avoided by the SINR-basedFFR which we evaluate in the following section.

4.4 SINR-based FFR

In this section, we consider two variants of theSINR-based fractional frequency reuse scheme: Thepure SINR-based scheme without any coordination in-between cell sectors and basestations, and the samescheme with additional coordination among cell sectorsof the same basestation based on the interference graph(zero tier coordination). In the uncoordinated case, the

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Fig. 13: SINR-based FFR: Throughput [kBit/s],thup = 25 dB, thup = 15 dB, 0-tier coordination

adjustable parameters are the lower and upper thresholdthlow and thup. In the coordinated case,DS offers anadditional degree of freedom.

Figure 12 plots the 5% throughput quantile overthe total sector throughput for different SINR thresh-olds. All points of one curve represent different valuesof thlow and are spaced5 dB apart with the firstpoint representingthlow = 5 dB and the last pointthlow = thup. Based on the previous results for zerotier coordination,DS is set to20 dB. From Fig. 12 wesee that the uncoordinated system can obviously notmatch the performance of the coordinated system withrespect to the aggregate throughput. In both cases,thup

and particularlythlow allow to trade-off the aggregatethroughput and the cell edge throughput.

The SINR-based FFR slightly outperforms thedistance-based FFR with respect to both the aggregatethroughput and the cell-edge throughput. Moreover, ithas a soft degradation of the performance when movingfrom the cell center to the edge, avoiding a sharp edgeas with the distance-based FFR. This is additionallyillustrated in Fig. 13 by the throughput within the obser-vation area. Summarizing the results, the performanceof a system with inter-cellular coordination can almostbe matched with regard to the total sector throughput.With respect to the cell border performance, the perfor-mance of the locally coordinated system is significantlyworse, as inter-cellular coordination allows a muchbetter control of the interference caused by neighboringbasestations.

5 Conclusion

Interference coordination is essential in OFDMA-basedcellular networks in order to achieve a high spectralefficiency and solve the problem of inter-cellular in-terference. In this paper, we showed that coordinationin-between neighboring base-stations almost matchesthe spectral efficiency of a global interference coor-dination. We further discussed several schemes basedon fractional frequency reuse. It was shown that theaggregate sector throughput of a pure FFR scheme is

only slightly better than that of a classical reuse 3system. The performance can greatly be improved byadditionally performing a local coordination in-betweensectors of the same basestation to almost match theperformance of the global interference coordinationscheme with respect to the overall spectral efficiency.The proposed SINR-based algorithm slightly outper-forms the distance-based algorithm with respect to theoverall spectral efficiency. It achieves about the samesector throughput as the global scheme while fallingshort with respect to the performance for terminals atthe cell border. This results in a spectral efficiency ofabout0.8 Bit/Hz/s for the locally coordinated reuse 1system as compared to about0.5 Bit/Hz/s for the reuse3 system.

6 AcknowledgmentsThis research was done in cooperation with Alcatel-Lucent Research and Innovation Department, Stuttgart.2

The author would like to thank Bozo Cesar, MartinLink, Stephan Saur, Michael Scharf, and Andreas We-ber for their valuable input.

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[8] H. Salgado, M. Sirbu, and J. Peha, “Spectrum sharing throughdynamic channel assignment for open access to personal com-munications services,” inProc. IEEE International Conferenceon Communications (ICC 1995), vol. 1, Seattle, WA, June 1995,pp. 417–422.

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[10] V. Erceg, L. Greenstein, S. Tjandra, S. Parkoff, A. Gupta,B. Kulic, A. Julius, and R. Bianchi, “An empirically based pathloss model for wireless channels in suburban environments,”IEEE Journal on Selected Areas in Communications, vol. 17,no. 7, pp. 1205–1211, July 1999.

[11] 3GPP TS 25.814,Physical layer aspects for evolved UniversalTerrestrial Radio Access (UTRA) (Release 7), 3rd GenerationPartnership Project, June 2006.

2Alcatel-Lucent Deutschland AG, Research & Innovation, Holder-ackerstr. 35, 70435 Stuttgart, Germany. Contact: Michael Tangemann(Michael.Tangemann@alcatel-lucent.de).