POLITECNICO DI TORINO DEPARTMENT OF ELECTRONICS AND TELECOMMUNICATIONS College of Electronic Engineering, Telecommunications and Physics (ETF) Master of Science in Telecommunication Engineering Masters Degree Thesis Advanced receivers for LTE/LTE-A systems with interference cancellation capabilities Supervisor Prof. Marina Mondin Ing. Bruno Melis Candidate Federico Pacifici March 2014 1 INDEX INTRODUCTION4 CHAPTER 1: From LTE to LTE-Advanced - PHY Overview6 1.1 Main concepts6 1.2Multi antenna techniques9 1.3 Transmission modes and transmission schemes10 1.4 Modulation and multiple access technique13 1.5 Downlink signals14 1.6 Downlink multi-antenna transmission17 1.6.1 Layer mapping18 1.6.2 Transmit diversity19 1.7 User Equipment categories20 1.8 A limiting factor of spectrum efficiency22 1.9 Inter cell Interference modeling: DIP values23 1.10 Channel profiles25 CHAPTER 2: ACTIVITIES IN 3GPP ON ADVANCED RECEIVERS27 2.1feICIC28 2.2 CRS-IM29 2.3 NAICS30 2.3.1 MMSE31 2.3.2 MMSE-IRC31 2.3.3 E-MMSE-IRC33 2.3.4Symbol level SIC34 2 2.3.5Bit level hard SIC35 2.3.6Soft Turbo SIC36 2.3.7ML receiver36 2.3.8R-ML38 CHAPTER 3: MMSE-IRC RECEIVER IN REAL SCENARIOS39 3.1 Overview40 3.1 General Architecture of the MIMO OFDMA simulator41 3.1.1 Data region Mapping/Demapping43 3.1.2 Subcarrier Mapping/Demapping45 3.1.3 IFFT/FFT calculation and cyclic prefix insertion/removal46 3.1.4 Pilots compensation47 3.1.5 Channel Estimation48 3.1.6 Space-time Encoder/Decoder50 3.2 Modeling MMSE-IRC51 3.2.1 MMSE-IRC for SFBC transmit diversity51 3.2.2 Building the MMSE-IRC receiver58 3.3 Performance of MMSE-IRC receiver61 3.3.1 Interfering signal modeled as Gaussian noise61 3.3.2 Real Interference signal Colliding pilot case63 3.3.3 Real Interference signal No Colliding pilot case67 CHAPTER 4: SUCCESSIVE INTERFERENCE CANCELLATION RECEIVERS69 4.1 Introduction and comparison69 4.2 SLIC implementation71 4.3 BLIC implementation76 4.4 SLIC and BLIC performance analysis79 3 CONCLUSION85 BIBLIOGRAPHY86 4 INTRODUCTION TheMasterThesiswaswrittenafteraninternshipperiodatTelecomItaliaS.p.A (WirelessAccessInnovationgroup).TheobjectiveofthisMasterThesisisanalyzing and simulating advanced receiver schemes with interference rejection capabilities that representoneofthenextinnovativestepinthephysicallayerofLTE/LTE-Asystems providinghigherthroughputespeciallyatthecelledge.Severalreceiverschemesare analyzedandsomeofthemaresimulatedtoobtainperformanceresultsintermsof Throughput and Raw BER. The selected receivers are chosen considering thetrade-off between complexity and expected gains.AlowcomplexityversionoftheMMSE-IRCreceiverhasbeenimplementedinalink level simulator specific for the LTE system, so performance results have been obtained showing interesting featuresand using a low complexitytechnique for the estimation oftheinterferencecovariancematrix.MMSE-IRChasbeenimplementedasan independentblocktosimplifythedevelopmentofinnovativereceiversthatuseitas elementary building block. The MMSE-IRC receiver outperforms the classical detection schemesthattreattheinter-cellinterferenceasGaussiannoise,especiallyincaseof nocollidingpilotsbetweentheservingandinterferingcells.MMSE-IRCisalsoa fundamentalblockofsuccessiveinterferencecancellationreceiversoperatingat symbol level (SLIC, Symbol Level Interference Cancellation) and bit level (BLIC, Bit Level Interference Cancellation). In a second step of the analysis SLIC and BLIC receivers have beenimplementedinasimplifiedlinklevelsimulatorbasedonMATLABandthe simulatedperformancesarecomparedwiththeotherconsideredreceivers.The analysisshowedthat,eveniftheSLICreceivercomplexityishigherthanMMSE-IRC one, it provides some gain especially in the low SINR region, while for higher SINR, the successiveinterferencecancellationfunctionalitymustbeswitchedofftoavoidthe error propagation effect. BLIC is more powerful, but its complexity is very high because it performs the channel decoding also for the interfering signals. The Master Thesis is structured into four chapters. In the first chapter, a Physical Layer overview of LTE and LTE-Advanced systems is provided, focusing on the aspects that have been considered 5 for the receiver implementations. Chapter two gives an overview of the activity carried outby3GPPonadvancedreceivers.Thethirdchaptershowsthealgorithmandthe implementationoftheMMSE-IRCreceiverintheLTElinklevelsimulator,discussing alsotheperformanceresults.ThelastchapterdescribestheSLICandBLICreceivers, showing simulation performance in terms of throughput and Raw BER. 6 CHAPTER 1: From LTE to LTE-Advanced - PHY Overview 1.1 Main concepts LongTermEvolution(LTE)isamobiletelecommunicationsystemdesignedtodrive theevolutionfrom3Gto4Gwirelesscommunicationtechnologies.These developmentsincludeallthenewesttechniquesthatcanprovidenewservicesto manyusersincomplexscenariosensuringthegrowingusersexpectation.Many technicalaspectsarestandardizedandtherearealotofresearchgroupsand companiesthatinvestinthesefields,moreovertheevolutiontrackingandthe dominant standards are the result of many partnerships inside 3GPP. In the last years, there was a strong evolution in terms of competition between mobile operators, new frequenciesallocation,newadvancedtechnologies,creatinganinnovativeand revolutionary market.Inthiscontext,thenaturaldevelopmentofmobilecommunicationwasdrivenbythe necessitytoenableinternetconnectivityformobileusers,creatingthemobile broadband.ThisisthemajordriverfortheevolutionofLTEthatprovideinternet protocolservices.PacketswitchedservicesandIPareguidelinesforaradiointerface thatsupportnewdesignparameterssuchas:highdatarate(closetoGbit/s),low latencyandhighcapacity.Notethat,from the mobilesystem operator perspective,it is not only important the peak data rate to end users, but also the total data rate that can be provided on average from each deployed base station and per hertz of licensed spectrum,sothespectralefficiency.Anotherimportantconstrainthathastobe satisfied is the Quality of Service for the end users.AllofthesedesignparametersinfluencedthedevelopmentofLTE,moreoverthereis anincreasingdemandformorespectrumresources,soinnovativemobilesystems need to operate in different frequency bands with spectrum allocation of different size and fragmentation. Onemaintargetfortheevolutionofmobilecommunicationistoprovidethe possibilityforhigheruserdataratescomparedtowhatisachievablewith3G 7 standards. Another important target is to provide higher data rates over the entire cell area, including users at the cell edge. Theoretically, the maximum rate is limited by the channelcapacitythatdependsonthechannelbandwidthandonthesignaltonoise ratio,inpresenceofAWGNnoise.Thisisanoiselimitedscenario,inwhich,thedata ratesarealwayslimitedbytheavailablereceivedpowerorbythereceivedsignal power to noise power ratio. When the bandwidth utilization is low, so the data rate is lower than the available bandwidth, increasing the data rate requires a higher received power,soanincreaseintheavailablebandwidthdoesnotsubstantiallyimpactwhat received signal power is required for a certain data rate. On the other hand, in the case of high bandwidth utilization, when the data rates is equal or higher than the available bandwidth,anincreaseofdataraterequiresamuchlargerincreaseinthereceived signalpower,soanincreaseinthebandwidthwillreducethereceivedsignalpower requiredforacertaindatarate.Inconclusion,thetransmissionbandwidthshouldat least be of the same order as the data rates to be provided. Fixingatransmitpower,toincreasethereceivedone,itispossiblereducethe attenuations,decreasingthedistance,planningsmallcellsandincreasingthenumber ofcells.Atthereceiverside,anotherusefultechniquetoprovidehighdataratesis using additional antennas, known as receive antenna diversity. Even at transmit side it ispossibletousemultipleantennas,socombiningsignalsreceivedatthedifferent antennasthesignaltonoiseratiocanbeincreasedinproportiontothenumberof antennas, allowing higher data rates. Multiple transmit or receive antennas techniques are efficient up to a certain level beyond which there is only a marginal increase in the datarates.Thislimitcanbeavoidedusingmultipleantennasatboththetransmitter andthereceiverside,usingthespatialmultiplexingorMIMO.Therearealsoother techniques,forexamplesfocusingthetotaltransmitpowerinthedirectionofthe receiver or reducing the noise power density improving the receiver design.Inthepreviouscases,theAWGNnoiseisthemainnegativecontribution,butinreal scenarios,especiallyinmobilecommunicationfields,theinterferencefrom transmissions in neighboring cells, called inter cell interference, is the dominant source of radio link impairment that usually occurs with a high traffic load. In addition to inter 8 cellinterference,therecouldbeanotherkindofinterference,calledintracell interference in which the useful signal is interfered by other signals within the current cell. In this case, the maximum data rate that can be achieved in a given bandwidth is limited by the SINR (Signal power to Interference and Noise Ratio).Oneimportantdifferencebetweeninterferenceandnoiseisthatinterference,in contrasttonoise,typicallyhasacertainstructurewhichmakesit,atleasttosome extent, predictable and thus possible to further suppress or even remove completely. Moreadvancedtopicsaboutinterferencecancellationwillbeaddressedcarefullyin thenextchapters,emphasizingsomeaspectsthatarethemainjobofthisMaster Thesis, focusing on the implementations and performances of advanced receivers able to cancel interferences in various scenarios. Fromtheoperatorpointofview,bandwidthisascarceandexpensiveresource,so telecomoperatorwouldliketoprovideveryhighdatarateswithinalimited bandwidth.Onewaytoincreasethedatarateistousehigherordermodulations.In 3Gsystems(i.e.WCDMA)isusedtheQPSKmodulation,nowadayshighorder modulationssuchas16QAMor64QAMareusedinHSPAtoimprovethebandwidth utilization, providing higher data rates within a given bandwidth at the cost of reduced robustness to noise and interference. Higher order modulation are normally combined with channel coding giving more efficiency, paying attention that an additional channel coding applied by using a higher order modulation scheme such as 16QAM may lead to an overall gain in power efficiency compared to the use of QPSK. Setting a SINR there is an optimal choice of modulation and channel coding to obtain the highest bandwidth utilization.Widerbandtransmissionsaresubjectedtofrequencychannelselectivitythatcorrupt the frequency domain structure of the signal, leading to higher error rates for a given SINR.Itisnecessarytodesignatransmissionschemethatavoidsfrequencychannel selectivitywithlowcomplexity.ThisgoalcanbereachedbyOFDM.Thisscheme providesalotofotherbenefitssuchasrobustnessagainstIntersymbolInterference (ISI) through cyclic prefix insertion, IFFT/FFT digital processing, user multiplexing, multi access etc.9 Using an OFDM scheme, it is possible to estimate the frequency-domain channel taps directly inserting known reference symbols or pilot symbols at regular intervals within theOFDMtime-frequencygrid.Knowingthereferencesymbols,thereceivercan estimatethechannelcoefficientsaroundthelocationofthereferencesymbols.The referencesymbolsaremappedintimeandfrequencydomaininagridwithahigh densitytocombathighfrequencyandtimeselectivity.Inthenextchaptersan advanced channel estimation algorithm will be explained. 1.2Multi antenna techniques Transmission with multiple transmit and receive antennas (MIMO) is supported in the downlink with two or four transmit antennas and two or four receive antennas, which allow for multi-layer transmissions with up to four layers. Both Single User MIMO (SU-MIMO) and Multi-user MIMO (MU-MIMO) are supported in the 3GPP specifications. In thecaseofSU-MIMO,thetransmissionresourcesoverthedifferentantennasare allocated to one user only, while in case of MU-MIMO the transmission resources are allocatedtodifferentusers.TheSU-MIMOisthenusedinordertoincreasetheuser peakdatarate(orcoverage),whileMU-MIMOisusedtoincreasetheaveragedata rate per sector. In particular the following multi-antenna transmission techniques are supported in the LTE Release 8 downlink standard: Transmit Diversity (SFBC), Spatial Multiplexing with a singleuse(SU-MIMO),SpatialMultiplexingwithtwousers(MU-MIMO),CDD (superimposedtoopenloopspatialmultiplexing),LinearPrecoding(bothforsingle layer or multiple layer transmission), single layer Beamforming.TransmitdiversityisbasedonthesocalledSpace-FrequencyBlockCoding(SFBC), complemented with Frequency Shift Transmit Diversity (FSTD) in case of four transmit antennas(MIMO4xn).Transmitdiversityisusedbycommondownlinkcontrol channels to provide additional diversity, as for these channels dynamic scheduling and H-ARQarenotapplicable.However,transmitdiversityisalsoappliedtouser-data 10 transmission,inparticularforcelledgeusersthatexperiencelowSignalto Interference plus Noise Ratio (SINR) values. Incaseofspatialmultiplexing,uptofourantennasatboththetransmitter(base station) and the receiver (terminal) side are used to provide simultaneous transmission of multiple parallel data streams, also known as layers, over a single radio link, thereby significantly increasing the peak data rates that can be provided over the radio link. As anexample,withfourbase-stationtransmitantennas,andacorrespondingsetof(at least) four receive antennas at the terminal side, up to four layers can be transmitted inparalleloverthesameradiolink,effectivelyquadruplingthepeakdataratewith respect to a single antenna system (i.e. SISO). 1.3 Transmission modes and transmission schemes In LTE Release 8 and LTE Release 10 (i.e. LTE Advanced), nine transmission modes are definedandtwodifferenttransmissionschemesareallowedineachtransmission mode.Thereferencetransmissionschemeiswhatisintendedforthetransmission mode and the other is for fallback operation.In 3GPP specifications the term antenna port is often used instead of antenna since, by meansofantennavirtualization,two/multiplephysicalantennascantransmitthe same information and hence make one antenna port. An antenna port is defined by its associatedReferenceSignal(RS)pattern.Thefollowingantennaportsaredefinedin Release 10:-Cell specific RS (antenna ports 0,1,2,3); -Multicast/BroadcastoverSingleFrequencyNetwork(MBSFN)RS(antenna ports 4); -UE-specific RS for single layer beamforming (antenna ports 5); -Positioning RS (antenna ports 6); -UE-specific RS for multi-layer beamforming (antenna port 7,8,9,10,11,12,13,14) -Channel state Information RS (CSI-RS) (antenna port 15,16,17,18,19,20,21,21); 11 Table1summarizesthetransmissionsschemescorrespondingtoeachtransmission mode. Downlink Transmission Mode Reference Transmission SchemeFallback Transmission Scheme Notes Mode 1Single antenna portSingle antenna port LTE Rel.8 Mode 2Transmit diversityTransmit diversityLTE Rel.8 Mode 3Open-loop spatial multiplexingTransmit diversityLTE Rel.8 Mode 4Closed-loop spatial multiplexingTransmit diversityLTE Rel.8 Mode 5Multi-user MIMOTransmit diversityLTE Rel.8 Mode 6Closed-loop rank=1 precodingTransmit diversityLTE Rel.8 Mode 7Single-antenna port; port 5Transmit diversity or single-antenna port LTE Rel.8 Mode 8Dual layer transmission or single layerTransmit diversityLTE Rel.9 Mode 9Up to 8 layer transmissionTransmit diversityLTE Rel.10 Table 1: Downlink Transmission Mode Amongthetransmissionmodesdefinedinthe3GPPstandard,TransmitDiversity (Mode2)andOpenLoopSpatialMultiplexing(Mode3)aresupportedinthefirst equipmentandterminalimplementationsandthusareofimportancefortheinitial roll-outoftheLTEnetwork.Switchingbetweenthesetwomodesisdecidedbythe networkasafunctionofthechannelconditions,whichisknowntotheeNodeB throughthechannelstateinformationreportedbytheUE(CQIandRI).Theaccuracy of RI reporting, which indicates the estimated number of simultaneous layers that can be received by the UE, is a critical information for the optimal usage of TxD and SM in a real LTE network. 12 This figure shows how is convenient to switch in a transmit diversity mode when SINR is low. Figure 1: Transmit Diversity and Spatial Multiplexing modes TheLTEphysicallayeroffersdatatransportservicestohigherlayers.Theaccessto theseservicesisthroughtheuseofatransportchannelviatheMACsub-layer.The physical layer is designed to perform the following functions: Error detection through CRC and indication to higher layers FEC encoding/decoding of the transport channel Rate matching Hybrid ARQ (with soft-combining at the receiver) Power weighting of physical channels Modulation and demodulation of physical channels Mapping onto physical channels Multiple Input Multiple Output (MIMO) antenna processing RF processing Figura 2: LTE Physical Layer 13 1.4 Modulation and multiple access technique TheLTEradiointerfaceadoptstheS-OFDMA(ScalableOFDMA)asmodulationand multipleaccesstechniquewithfixedsubcarrierspacingfequalto15KHz.Thetotal numberofsubcarriers(i.e.theFFTsizeNFFT)isproportionaltothechannel bandwidth.Forexample,incaseofachannelbandwidthBW=10MHztheFFTsizeis 1024. In this case the number of subcarriers used for transmission (e.g. data, pilots or control)isequalto600,whiletheremainingsubcarriersareleftunused,fortheDC subcarrierandfortheguardsubcarrierspositionedattheedgesofthetransmission spectrum. Table 2 summarizes the LTE numerology for different channel bandwidths. Table 2: LTE numerology AnimportantcharacteristicoftheLTEradiointerfaceisthattheframedurationand Transmission Time Interval (TTI) are harmonized with those of UMTS/HSDPA system. In particulartheframedurationisequalto10mswhilethesubframeperiod,which corresponds to the Transmission Time Interval (TTI), is equal to 1 ms (compared to the 2 ms of HSPA). Each subframe is divided in two slots, where each slot has a duration of 0.5 ms. Also the sampling frequency of the baseband (BB) signals are harmonized: for UMTS/HSPAthebasebandsignalissampledat 3.84MHz,whileforLTE thebaseband sampling frequency is equal to m/n3.84 MHz, where m and n are integer factors that 14 depend on the LTE channel bandwidth. These features reduce the complexity and the cost of dual mode terminals that will support both radio interfaces. 1.5 Downlink signals A downlink signal corresponds to a set of resource elements used by the physical layer but does not carry information originating from higher layers.Thefollowingdownlinkphysicalsignalsaredefinedinthestandard:Referencesignal and Synchronization signal.Threetypesofdownlinkreferencesignals(RS)aredefined:Cell-specificreference signals(CRS),MBSFNreferencesignals,associatedwithMBSFNtransmission,UE-specific reference signals.Thecellspecificdownlinkreferencesignals(CRS)consistofknownreferencesymbols inserted in the first and third last OFDM symbol of each slot in the case of Normal CP. Figure 3: Pilot pattern for a SISO system Thereisonereferencesignaltransmittedperdownlinkantennaport.Thenumberof downlinkantennaportsPequals1,2,or4.TheRSofdifferentantennaportsare orthogonal among each other because resource elements used for RS transmission of one antenna port are not used for any transmission by the other antennas (i.e. are set to zero power for the other antennas).15 Figure3,Figure4andFigure5,respectivelyshow,thepilotpatternforaSISOcase whenanormaloranExtendedprefixcyclicisused,theCRSsignalsfortwotransmit antennas (MIMO 2x2) and finally CRS signals for four transmit antenna (MIMO 4x4). The cell specific RS sequence is a PN (pseudo random) sequence defined by a length-31 Gold sequence. The pseudo-random sequence generator is initialised with a value that depends on the cell identity (cell-ID) so that different PN sequences are associated to different cells. In this way the RSs of different cells have low values of cross-correlation andthus theinterferencefromneighboringcellscanbereduced byproperaveraging on frequency adjacent reference symbols received at the UE. Figure 4: MIMO 2x2 CRS pattern Frequencyhopping(FH)canbeappliedtothecell-specificreferencesignals.The frequency hopping pattern has a period of one frame (10 ms). Each frequency hopping pattern corresponds to one cell identity group.TheLTEstandardforeseesalsoUE-specificreferencesignals,alsodenotedinthe technicaldocumentsasDeModulationReferenceSignals(DM-RS).TheDM-RSsare introducedforthesupportofbeamformingtechniques.TheeNodeBcansemi-staticallyconfigureaUE tousethe dedicatedreferencesignalas thephasereference for data demodulation of a single codeword. DL control signalling is located in the first n OFDM symbols (ns 3) of a subframe and consists of:-Number n of control OFDM symbols per subframe (PCFICH); 16 -Transport format, resource allocation and hybrid-ARQ information (PDCCH); -Uplink scheduling grant (PDCCH) -ACK/NACK in response to uplink transmission (PHICH) Note that there is not mixing of control signaling and shared data in an OFDM symbol. Figure 6 shows the mapping between Control and Data symbols. Figure 5: MIMO 4x4 CRS pattern Controlchannelsareformedbyaggregationofcontrolchannelelements(CCE),each control channel element consisting of a set of resource elements. The modulation used for all control channels is QPSK.17 Multiple physical downlink control channels are supported and a UEmonitors a set of control channels. Figure 6: Control and Data REs 1.6 Downlink multi-antenna transmission Spatialmultiplexing(SM)ofmultiplesymbolstreamstoasingleUEusingthesame timefrequencyresources,alsoreferredtoasSingle-UserMIMO(SU-MIMO)is supportedintheLTEstandard.Spatialmultiplexingofmultiplesymbolstreamsto different UEs using the same time frequency resources, also referred to as MU-MIMO, isalsosupported.IngeneralSU-MIMOisbeneficialforincreasinguserthroughputor coverage, whilst MU-MIMO is exploited for increasing the aggregate cell throughput. InadditiontoSU-MIMOandMU-MIMO,thefollowingspatialprocessingtechniques are also supported in the LTE Release 8 standard: Codebook based precoding, Transmit antennadiversitybasedonSFBC(Space-FrequencyBlockCoding),Singlelayer Beamforming and Cyclic Delay Diversity (CDD). In the following a short description of these multi-antenna transmission techniques is provided. 18 1.6.1 Layer mapping Multi-antennatransmissionwith2and4transmitantennasissupported.The maximumnumberofcodewordistwo,irrespectivetothenumberofantennas,with fixedmappingofcodewordstolayers.IntheMIMOterminologyonecodeword representsonedatastreamthatisindependentlyencodedandmodulatedunderthe control of the AMC (Adaptive Modulation and Coding) procedure. The mapping of the codewords to the layers depends on the rank of the channel and is performed by a specific block denoted as layer mapping. The layer mapping operation is depicted in Figure 7, where CW1 and CW2 are the first and the second codeword respectively and the layer mapping block is represented by thedottedboxinbluecolour.Theoutputofthelayermappingoperation(e.g.the layers) is provided to the block that performs the precoding. Figure7: Layer mapping for two transmit antennas TheFigure8showsthelayermappingoperationforthecaseoffourtransmit antennas. Figure 8: Layer mapping for four transmit antennas 19 1.6.2 Transmit diversity Transmitantennadiversity(TxD)isdesignedtoimprovetransmissionreliabilityand coverageandistypicallyusedforcelledgeusersthatexperiencelowvaluesofSINR and for which it is not advantageous the use of spatial multiplexing. TheLTEstandardincludestwodifferenttechniquesbasedonSFBC(SpaceFrequency Block Coding) for the case of two and four transmit antennas respectively: SFBC for 2-Tx antennas, SFBC combined with FSTD for 4-Tx antennas. IncaseoftwotransmitantennastheSFBCtechniqueisbasicallytheAlamouticode appliedinthefrequencydomainovertwoadjacentOFDMsubcarriers.TheFigure9 showstheprincipleofSFBCencodingwhereS1andS2arethemodulatedsymbols comingfromthelayermappingblock.Itmustbenotedthatonlyonecodewordis transmitted when the TxD technique is used. Figure 9:SFBC technique for two transmit antennas AnimportantfeatureoftheAlamouticodeisthatonlysimplelinearoperationsare needed at the receiver for decoding. IncaseoffourtransmitantennastheLTEstandardadoptsacombinationofthe AlamouticodeandtheFrequencySwitchingTransmitDiversity(FSTD)technique.The Figure10showstheprincipleofSFBC+FSTDencodingwhereS1,,S4arethe modulated symbols coming from the layer mapping block. Notice that also in this case only one codeword is transmitted. BasicallytheSFBC+FSTDtechniqueconsistsintheapplicationoftheAlamouticode over pair of antennas. 20 Figure 10: SFBC+FSTF technique for four transmit antennas The Alamouticodeisappliedovertheantennas 1and 3 forsymbolsS1 and S2,while forsymbolsS3andS4thecodeisappliedovertheantennas2and4.Theantenna pairing(1,3)and(2,4)isdoneinordertobalancethedifferentpilotdensitythatis lower for antenna 3 and antenna 4 compared to antenna 1 and antenna 2. 1.7 User Equipment categories Fromtherelease 8to therelease10user terminalssupportdifferentfeatures having differentphysicallayercapabilities.InLTErelease8/9,forexample,thelow-end category 1 does not support spatial multiplexing, while the category 5 supports the full set of features in the release 8/9 physical layer specifications. In LTE release 10, more usefulinterestingtechniquesareused(i.e.carrieraggregation),providinghigher performance. 21 In Table 3 are showed the eight categories from 1-5 (LTE Release 8/9/10) to 6-8 (LTE-Advanced Release 10). Table 3: UE Category Inmoredetail,forcategoriesfrom1to5,itisshowedaTable4containingthe downlinkphysicallayer parametersforeachcategory.ThesecondcolumninTable4 defines the maximum number of DL-SCH transport blocks bits that the UE is capable of receiving within a DL-SCH TTI of 1 ms. In case of spatial multiplexing, this is the sum of thenumberofbitsdeliveredineachofthetwotransportblocks.Thethirdcolumn represents the maximum number of DL-SCH transport block bits that the UE is capable ofreceivinginasingletransportblockwithinaDL-SCHTTI.Thefourthcolumn represents the total number of soft channel bits available for H-ARQ processing while thelastcolumngivesthemaximumnumberofsupportedlayersforspatial multiplexing per UE. 22 Table 4: Downlink Physical Layer parameters ItispossibletonoticethataCategory3userequipmentiscapableofsupportinga downlink peak throughput of about 102 Mbit/s (i.e.102048 received bits in one 1 ms) andthatitcansupportspatialmultiplexingwithamaximumoftwolayers.Thehigh-endterminalscorrespondenttothecategory5cansupportapeakthroughputof about 300 Mbit/s with spatial multiplexing over four layers (these terminals thus need to be equipped with four receive antennas). 1.8 A limiting factor of spectrum efficiency The ever increasing user density in cellular systems coupled with the unitary frequency reusefactorselectedfortheLongTermEvolution(LTE)standardhavemade interference(bothinter-cellandintra-cell)themainlimitingfactorofspectrum efficiencyinLTE-Advanced(LTE-A)system,andInterferenceCancellation(IC)one possible solution that need to be addressed in LTE-A receivers. In this Master Thesis I focusmyattentiontoMultipleInputMultipleOutputOrthogonalFrequencyDivision Multiplexing (MIMO-OFDM) schemes and Space Frequency Block Code (SFBC) encoded schemes, and I will describe the corresponding receiver structures.As far as the interference is concerned, depending on the transmission conditions and theconstraintsimposedbythetransmissionstandard,areceiveraffectedby interference may have different degrees of knowledge of the interference signals, and 23 as a consequence different IC strategies will be possible. In general, the more complete the knowledge of the characteristics of the interfering signals, the more elaborate the IC strategies that can be implemented, the better the achievable performances. Iamdealingwithamulti-antennascheme,withtypically2antennasattheuser terminaland2or4antennasatthebasestation.Theavailabilityofmultiple transmissionantennaswillbetypicallyusedtoimprovethroughputandcapacity, transmittingmultipleinformationstreamsthatwillbereceivedoverlappedatthe receiving antennas. For this reason the considered receivers will have, as a first step, to beabletoperformwhatwewilldenoteasMIMOequalization,i.e.toseparatethe individual information streams, cancelling the mutual interference (this scenario exists alsoinabsenceofanyintra-cellorinter-cellinterference),andgeneratinganinitial estimateofthetransmittedsymbols,thatwillthenbefedtothesubsequentsoft-demapper. Inpresenceofprohibitivetransmissionconditions,likeatthecellboundary,the presenceofmultipleantennasmayalsobeusedtoimproveperformancesby introducingredundancyonthespaceandfrequency(ortime)dimensions,usingaso calledSpaceFrequencyBlockCode(SFBC).InpresenceofaSFBC,theinter-stream interference is typically null or minimal, and, as a consequence, non-iterative receivers are often employed. 1.9 Inter cell Interference modeling: DIP values Network interference statistics are computed using geometry factor G, defined as: whereorjIistheaveragereceivedpowerfromthej-thstrongestbasestationimplies(1orI is the serving cell average received power), o2 is the thermal noise power over the 221 1 o += ==BSNjorjorocorIIIIG24 received bandwidth, and NBS is the total number of base stations considered including the serving cell.Inadditiontogeometry,anothermeasure,referredtoastheDominantInterferer Proportion(DIP)ratio,wasagreedasakeyparameterfordefiningtheinterference profiles.DIPwasdefinedas theratioof thepowerofagiveninterferingcelloverthe total other cell interference power. DIPofsynchronized,andasynchronizedinterference, siDIP , aiDIP isexpressedas follows: where the total inter-cell interference plus noise is given by: and NBS = NS + Na is the total number of eNodeBs considered including the serving cell. DIPratiostatisticshavebeenderivedobtainingbothunconditionalDIPCDFsand conditionalmedianDIP values,thelatterconditioned onvariousgeometryvalues.An interferenceprofilewasdefinedonthebasisofaveragingunconditionalmedianDIP values submitted by the different companies.DIP values conditioned to the geometry valueshavealsobeensubmittedbythedifferentcompanies.Startingfromthese values, the interference profiles that have been defined as part of the 3GPP feasibility study to assess link level performance of MMSE-IRC receivers, are showed in Table 5. ( 1)sorisiocIDIPI +=aor iaiocIDIPI=2 1 s a N Ns aocor j or jj jI I I N= == + + 25 Table 5: Conditional DIP values 1.10 Channel profiles Three channel profiles have been defined in 3GPP for UE and BS conformance testing. These profiles are also used in the link level simulations. The delay profiles are selected toberepresentativeoflow,mediumandhighdelayspreadenvironments.The frequency selectivity of the channel is proportional to the delay spread. Table 6: 3GPP Channels The link level simulations have been done for the Extended Pedestrian A (EPA) channel profile defined by the 3GPP. Table 7: EPA Channel ProfileGeometrySynchronized NWAsynchronized NW DIP1DIP2DIP Based on conditional median values 0 dB geometry-3.1-5.4-3.1 -3 dB geometry-2.8-7.3-2.8 -2.5 dB geometry 26 Table 8: EVA channel The channel is assumed constant in each TTI (Transmission Time Interval of 1 ms).Thecorrelationofthefadingprocessesissetaccordingtothethreecasesdefinedin 3GPPfortheconformancetests(TS36.101andTS36.104)oftheequipments(low, medium and high correlation): Table 9: Correlaton of fading processes Theoand|correlationvaluesare,respectively,thecorrelationcoefficientatthe transmitter and the correlation coefficient at the receiver. Thefadingcorrelationismainlydeterminedbytwofactors:antennacharacteristics (e.g. distance, polarization) and propagation environment (e.g. number and position of thescatterers,presenceofLoS,angleofarrivalandanglespreadofthe electromagnetic waves). ThetransmissionschemesofLTEaredifferentlyaffectedbythecorrelation.In particulartransmitdiversity(TxD)appearsratherrobustwhilstSpatialMultiplexing (SM) suffers a severe performance degradation as the correlation increases. 27 CHAPTER 2: ACTIVITIES IN 3GPP ON ADVANCED RECEIVERS Thischapterprovidesanoverviewofactivitiescarriedoutin3GPPonthetopicof advanced receivers with interference cancellation/mitigation capabilities.The activities have been carried out mainly in the RAN4 group under the framework of four study/work items: IR, feICIC, CRS-IM, NAICS. Study ItemDescriptionFocus IR (Rel.11) Interference Rejection Focus onreceiverstructurestargetingspatial domaininterferencemitigation.IRC considered as a starting point. feICIC (Rel. 11) Further enhanced ICIC Heterogeneousnetworkscenarioswherethe interferenceis mainly caused by the CRS and Control Channels of the macro cell on the UEs connected to the small cells CRS-IM (Rel. 12) CRS Interference Mitigation(RP-130393)Analysesthecancellationoftheinterference causedbyCRSinsynchronizedhomogenous network scenarios NAICS (Rel. 12) Network Assisted Interference Cancellation Suppression (RP-130404) NAICSissimilartotheapproachofCRS-IM. ThemajordifferenceforNAICSisthatthe interferencemitigationisnowtargetednot onlyforinterferingCRSbutalsofor interferingPDSCHconsideringalsopossible improvementsderivingfromnetwork assistance 28 2.1feICIC InthefeICICcasethefocusisontheheterogeneousnetworkscenarioswherethe interference is mainly caused by the CRS and Control Channels of the macro cell on the UEs connected to the small cells.The main IC candidate techniques for the implementation at the UE side include: -Interferencecancellation:signalregenerationandsubtractionapplicableto CRS, PBCH, PSS/SSS; -Puncturing; receiver that punctures REs of the wanted signal of the serving cell that are interfered by CRS REs received from one or more dominant interfering cells. InthecaseofCRSinterferencecancellation,theprocedurerequires:thechannel estimationfromtheinterferingcells,regenerationofalltheinterferingcellsCRS signals and subtraction.Puncturing is not applicable in several scenarios, e.g. with colliding CRS in non-MBSFN ABS because CRE REs of the serving cell cannot be punctured. For SFBC and SFBC-FSTD, twoREsusedshouldbepuncturedsimultaneouslywhenoneofthemwas contaminated.Intheothercases,itsetstheLLRofbitsofREsundergoingstrong interference as zero. TheresultsshowthebetterandrobustperformanceandversatilityoftheCRS cancellingreceiverovertheCRSpuncturingreceivers.AlsoforPDSCHdemodulation the CRS cancelling receiver outperforms the CRS puncturing receivers. CRS puncturing receiverperformsreasonablyforsinglenoncollidinginterferer,butfortheother scenariositdoesnotperformwell.TherelativelypoorperformanceoftheCRSRE puncturing receiver for transmission mode 2 is because strong interference on one RE affects demodulation of the two symbols that are transmitted through the affected RE via SFBC encoding. 29 2.2 CRS-IM InterferenceMitigation(IM)ofCell-SpecificReferenceSignals(CRS)hasbeenstudied in the Rel-11 Work Item on feICIC, where interference from CRS is dominant assuming data RE muting in ABS subframes. A new study item has been started in 3GPPon CRS interference mitigation (IM) in homogeneous network deployments. The main objectives of this Study Item are: -identify the partial traffic loading levels, other realistic system level parameters (e.g. traffic and interference models, time and frequency offset between cells) andperformancemetricsforstudyingthefeasibilityofCRS-IMina synchronized homogenous network; -identify the baseline receiver which can be used for evaluating the gain of CRS -IMinasynchronizedhomogenousnetworkconsideringthereuseofCRS-IM receiver assumed for Release 11feICIC and the reuse of MMSE-IRC receiver as the baseline receiver; -evaluatethesystemlevelandlinklevelgainsofCRS-IMwithrespecttothe baselineMMSE-IRCreceiverinasynchronizedhomogenousnetwork deploymentunderthevariousloadinglevelsidentified(e.g.gainsofCRS-IM from 1 and 2 aggressor cells CRS shall be evaluated and compared). The objectives of the study item explicitly indicate that only Release 11 CRS assistance information should be assumed to be available.It can be seen that the CRS assistance information consists of a list of cells which are to be considered as candidates for CRS interferencemitigation.Therefore,foreachcelltheinformationrelatedtotheCRS transmission(i.e.thephysicalcellID,antennaportcountandMBSFNconfiguration) are provided to the UE. A way forward on CRS-IM performance evaluation has been agreed. The first proposal isthereuseofCRS-IMreceiverassumedforRelease11feICICtomitigateCRS interferenceofuptotwocells.ThesecondsolutionisthereuseofMMSE-IRCbased receiverwithinterferencecovariancematrixestimation,herethereceiverdoesnot differentiate CRS or data interference when suppressing them.30 Theproposedreceiverschemefortheexecutionofthelinklevelsimulationsisthe MMSE-IRC with/without CRS-IM. Concerning the CRS-IM part of the receiver, basically itconsistsintheregenerationandsubtractionoftheCRSsignalfromonlythe1stor boththe1stand2ndstrongestinterferingcell.Apossiblereceiverimplementationis depicted below. A possible work item on this activity can follow. Figure 1: MMSE-IRC with CRS-IM 2.3 NAICS NAICS is similar to the approach of CRS-IM. The major difference for NAICS is that the interferencemitigationisnowtargetednotonlyforinterferingCRSbutalsofor interfering PDSCH. Objectives of this Study Item for RAN4 are: -IdentifyreferenceIS/ICreceiverswithandwithoutnetworkassistance,and evaluatetheirperformance/complexitytrade-offandimplementation feasibility; -Analyzecomplexityand feasibilityofbasicreceiverstructures:basedonlinear MMSE-IRC,successiveinterferencecancellation,andmaximallikelihood detection are considered as a starting point for reference IS/IC receivers; -BasedontheRAN1scenariosagreeonco-channelinterandintra-cell interference models for link-level simulation; -Evaluate the link-level gain over baseline Rel-11 linear MMSE-IRC receivers and Rel-11 non-linear receivers required for feICIC; 31 -Indicate(toRAN1)assumptionsonthe networkassistanceinformation forthe evaluated receivers under possible network coordination. Inthefollowingpartofthischapter,itwillbeshownabriefdescriptionofthemain advanced receivers with interference cancellation/mitigation capabilities. 2.3.1 MMSE TheRel-8/Rel-9baselinereceiver,MMSEreceiver,ignoresthefactthatinterfering signalsarespatiallycoloredsignal.MMSEreceiverstreatinterferenceaswhitenoise. AlongwiththechannelmatrixHforthedesiredsignal,onlyinterference-plus-noise power 2n I +oneeds to be estimated by the MMSE receiver. The MMSE receiver can be expressed as: ( ) x I HH H sn IH H12++ = o ThecomplexityoftheRel-8/Rel-9MMSEreceiverisgivenby:thechannelestimation and the matrix inversion. 2.3.2 MMSE-IRC Usingaproperspatiallycoloredinterferencemodel,anMMSEinterference rejection/combiningreceiver(MMSE-IRC)isexpectedtooutperformtheMMSE receiver in strong interference scenarios. InRel-11advancedreceiverSID,RAN4studiedtwoapproachesoftheMMSE-IRC receiverrealization.OneapproachistousedataREstoestimateoverallsignal-plus-interference-plus-noise covariance matrix n I sR+ +. In this case,The MMSE-IRC receiver has the form of: ( ) x R H sn I sH 1+ += 32 AsecondapproachtorealizetheMMSE-IRCreceiverisusingtheCRSorDMRSfrom theservingtransmittertoestimatethechannelmatrixHofthedesiredsignal,and using the differences of the received reference signal and the re-constructed reference signalwiththeestimateddesiredchannelontheCRSorDMRSREstoestimate interference-plus-noise covariance matrixn IR +: ( ) x R HH H sn IH H1++ = ( )( )e+ =RS l kl k l k l k l k n Ix H y x H y R,, , , , H TheRAN4Rel-11advancedreceiverstudyshowsthatCRSorDMRS-basedMMSE-IRC receiveroutperformsdataRE-basedMMSE-IRCreceiver.TheaboveMMSE-IRC approachescanbeappliedtointra-cellinterferencesuppressioninMU-MIMO scenarios as well as to inter-cell interference suppression. FortheRel-12NAICSSID,itwouldbealogicalextensiontostudythepossible performance gain of an MMSE-IRC receiver when the system assists UEs in performing better channel state information estimation, for both desired and interference signals. For example: -Incaseofdominantinterferencecellexistse.g.inHetNetcase,UEmay explicitlyestimatethechannelofdominantinterferencecell.Thus,the covariancematrix n IR +ofinter-cellinterferencecouldbecalculatedbasedon the channel estimation of dominant interference cell; -the accuracy of covariance matrix may also be improved by allowing averaging across multiple RBs, so the estimated received symbol is: x I H H HH H sPiIHi iH H112=|.|

\|+ + =o 33 2.3.3 E-MMSE-IRC EnhancedMMSE-IRCisanMMSE-IRCthatconsidersdifferentinterfererchannel estimatesandnewinterferenceknowledgefromnetworksignalingortroughblind techniques.E-MMSE-IRCcouldachievesignificantthroughputgainoverMMSE-IRC receiverforbothCRS-basedandDMRS-basedtransmissions,giventheassistancefor UE to perform channel estimation on interference signals and knowing the number of layers.Adisadvantageofthisreceiveristheperformancegainsinceitislowerthanothers receivers (ML, SLIC, CWIC) when SINR is low. In contrast, there are several advantages using E-MMSE-IRC: -limited complexity; -throughput gain is significant for high SINR; -otherreceiversrequiremoreadditionalassistanceinformation,introducing morecomplexityandlessrobustness(e.g.MLandSLICreceiverneed modulation of interference signals trough blind detection or DCI/RRC signaling). Inthiscontext,thereceivedsignalisgivenbythesuperpositionofoneusefulsignal and N-1 interferer signals with different precoding matrix and different amplitudes: 1, ,0Nk i i k ii k kiy H P x n == + where,iistheamplitudeofthesignaltransmittedfromi-thcell,, i kH isthechannel matrixofthei-thcellonthek-thtone/resourceelement(RE), , i kx isthesymbol transmitted by the i-th cell in the k-th tone and iP is the spatial precoding matrix used by the i-th cell and K is the total number of observed tones. The number of cells in this case is N with one serving cell and N 1 interferers. Theoperationscanbesubdividedincorereceiverprocessing(Channelestimation, CRS-IC, Detection, Decoding) and parameter extraction.34 Corereceiverprocessingincludessymbolleveldetectionofthedesiredcellssignals andTurbodecoding.Atthedetectorstage,Rel-11MMSE-IRCreceiverssuppressthe transmissionfrominterferingcellsbeforedetectingthedesiredsymbols.Thenulling operation is performed by a front end MMSE filter, W, and Wy is the linear estimate of thetransmittedsymbols.ForRel-11MMSEIRCreceivers,Wisconstructedusing:the channel estimation of serving cell and the total interference and noise estimated using CRSorDMRS.Incontrast,evenifE-MMSE-IRCreceiverperformsomesimilar functions, there are some key differences: -theinterferingsignalsaremodelledusingtheestimatedchannelsofthe interferers, using CRS-IC; -foreachsignal theprecodedmatrixis neededanditisobtainedusingUE-side blind estimation or network signaling; -theinterferersignalstrengthisextractedfromnetworksignalingorblind detection at the UE. IntheE-MMSE-IRCreceiverthecomplexityiscalculatedconsideringthechannel estimationcomplexity(CCE),theMMSE-IRCdetectioncomplexity(CFE),theFEC decodingcomplexity(CBE)forthecorereceiverandtheparameterextraction.The complexity is N(CCE) + CFE + CBE , while the complexity of MMSE-IRC is CCE + CFE + CBE. The MMSE-IRC complexity is lower than the E-MMSE-IRC one, since the channel estimation ismadewithoutCRS-IC,whileinE-MMSE-IRCthechannelestimationwithCRS-IC scaleslinearlywith the numberofinterferers.Tocompletion,CFE isthe detectionand interference cancellation complexity and CBE is the FEC decoding and turbo decoding. 2.3.4Symbol level SIC There are two types of successive interference cancellation (SIC) receivers: in the first one only symbol demodulation is involved in the SIC process and in the other one the FEC decoding is involved. It can be expected that, if the FEC decoding is involved in the SIC process, the performance will be improved compared to the one only using symbol demodulation. However, FEC decoding will require that all detailed coding information 35 andresourceallocationinformationoftheinterferencesignalbeavailabletotheUE receiver, this requires a lot of system coordination and signalling overhead.The symbol level SIC receiver can be expressed as: ( ) |.|

\| + ==Pii i nH Hs H y I HH H s112 ~ o where is~ is the quantized estimation of the interference signal.The symbol level SIC receiver needs to know the modulation order of the interference signal, power offset and (an estimate of) the channel matrix of the interferers as well. Thisrequiressystemassistanceinprovidingtheinterferencemodulationorderand providingmeanstoestimatetheinterferencechannelmatrix.Itisageneral understandingthatanSICreceivercanperformwellincasethattheinterference signal is much stronger than the desired signal. Therefore, SIC receivers are well suited for some inter-cell interference scenarios (like range extension in HetNet, or intra-cell interferenceinsomeMU-MIMOcases).However,forinter-cellinterferencein homogeneousnetworks,theinterferencesignalcangenerallybeexpectedtobe weakerornotmuchstrongerthanthedesiredsignal.Inthiscase,theperformance advantage of SIC receiver over MMSE-IRC receiver may be questionable. 2.3.5Bit level hard SIC The receiver attempts to detect and decode one by one the interferers of interest, also incaseofMU-MIMOand/orinter-cellinterferencecancellation.Thedecoded interferersaresubtractedstep-by-steptotheoverallsignal,obtainingattheendthe decoded useful signal. ThisreceivertakesadvantageoftheCRCattachedtoeachtransportblockbefore channelcoding:ifCRCcheckissuccessful,theblockhasbeencorrectlydecodedand the interfering signal can be reconstructed (minor the channel estimation errors). The 36 bitlevelhardSICtobeefficientneedstofindatleastoneinterfererthatcanbe decoded without error (in order to subtract its interference from the useful signal).As a result, the situations where the interference power is much higher than the useful signal power and/or when the interference has a robust MCS are favourable situations where it brings significant gains. In case the interference and useful signal have similar powers, the Hard SIC imposes the constraint that the MCS used by the first interferer bemorerobustthantheMCSusedforthesignalofinterest,asitwillneedtobe decoded under the interference of the latter. 2.3.6Soft Turbo SIC ThisreceiverschemeperformsthesoftdetectionandtheTurbodecodingoftheUE signals which are repeatedly subtracted from the received signal.An important parameter of these receivers is the number of Turbo-code iterations for each detection and decoding step.In the case of Turbo-SIC receivers (also in the Hard SIC),thevictimUEneedstoknowthefollowingtransmissionparametersofthe interferers:-PRB assignments; -MCS; -RNTI; -DMRS sequence (if demodulation is based on DMRS); -Precoding information (if demodulation is based on CRS). UptoRelease11,aUEcannotaccessanyofthesepiecesofinformationrelatedto another UE. Some mechanisms (e.g. a new signalling) then need to be introduced into the standard in order to provide this information to the victim UE. 2.3.7ML receiver Thisreceivertreatstheinterferenceasun-knowndeterministicQAMsignal.ML receiverscanjointlyestimatethedesiredsignalandtheinterferencesignals.Itis 37 generally understood that ML receivers provide an optimal performance compared to other receiver structure. SIC receivers can be viewed as sub-optimal realizations of ML receiverswithlesscomputationalcomplexitybutsomeperformancedegradationas compared to ML receivers.TheMLreceiver,liketheSICreceiver,requiresinformationofthemodulationorder and channel matrix of the interference signals. The ML receiver can be expressed as: { }21,.., , ,2 12 1min arg ,..., , , =O e =Pii is s s sPs H Hs x s s s sP where, O is the set of constellation points of the used modulations. It can be expected that the ML receiver would provide good performance in both intra-cell and inter-cell interference mitigation. However, when the number of layers of the desiredsignalplusinterferencesignalsislargeandwhenthemodulationordersare high, the full ML receiver is very computationally complex and may not be feasible to implement.Forexample,atotalofNS=4layerswithM=64constellationsizewill requireaboutMNs=644=16millionhypotheses.Thisisaverylarge numberof possible combinationsforaUEreceivertocheckthem.Someperformance-complexitytrade-offhastobetakenforthishighordermodulationandlargenumberoflayers.Some well-knownsub-optimalML-typereceivers,forexample,spheredetectors,couldbe considered as candidate. ML receiver can be easily extended to joint detection on desired and interfering signals withlimitedNetworkAssistance(NA)information.Forexampleifthechannel knowledgeandmodulationorderoftheinterferenceisavailable,interferingsignals couldbetreatedasdesiredsignalsandjointdetectedbyMLreceiver.Thereisno difference in ML receiver processing procedure.Assuming UE has the ML detection capability up to 2layers receptions, when UE is in cellcentrearea(highSNRregion),MLreceivercanbeusedtodetectthescheduled Rank 2 transmission. When UE move to cell edge area (low SNR region) and scheduled 38 withRank1transmission,thedominantinterferingsignalscouldbejointlydetected with limited additional NA information. 2.3.8R-ML Thisadvancedreceiverisareducedcomplexitymaximumlikelihoodreceiver.Itis basedonthejointdetectionofusefulandinterferencemodulationsymbolsin accordance to the ML criterion (e.g. sphere decoding, QR-MLD, MLM, etc.). . Assuming that there is only one strong interferer, the received signal is: 1 1 1 2 2 2= + + x x y H W H W nwhere,

is the useful channel matrix and

is the interferer channel matrix. The ML can be expressed as: ( ) ( ) ( ) ( )_ _ e e| | | |= ||\ . \ . 1 10 1( ) ( )() log logH Hi iib bLLR b e ey Hx R y Hx y Hx R y Hxx x where_k i(b ) denotesthesetoftransmitvectorswith( ) 0 1 = =ib k, k , ,andR isthe noise covariance matrix.Using a Rel.11 MMSE-IRC receiver, the interferer term (the second one inserted in the received signal) can be used to calculate the interferer plus noise covariance matrixRin this way: { }2 2 2 2H H HE = + R H WW H nn . Finally, about the R-ML, LLRs can be also represented by max-log approximation: ( ) ( ) ( ) ( ) ( )0 11 1_ _ e e ((= (( i iH Hi( b ) ( b )LLR b min minx xy Hx R y Hx y Hx R y Hx39 where | |1 1 2 2= H H W H W ,| |1 2=Tx x x , R is the interferer plus noise covariance matrix, y is the received symbols 2x1 matrix and_k i(b )denotes the set of transmit vectors with ( ) 0 1 = =ib k, k , . R-ML is a reduced complexity version of ML, but it is more complex than the previous receiver schemes, even if it provide sub-optimal performance. CHAPTER 3: MMSE-IRC RECEIVER IN REAL SCENARIOS 40 3.1 Overview Thischapterprovidesadetailedvisionofalltheaspectsthatledtoalowcomplexity implementationoftheMMSE-IRCreceiverinrealscenarios.Moreover,performance resultsareshowedandexplainedcarefully,takingcaretoselectrelevantresultsthat best show the behavior of the receiver. Atthestartingpoint,abriefanalysisofthesimulationplatformisprovided,focusing on some key blocks that are the core of a MIMO OFDMA link level simulator and that areusefulto understandthe MMSE-IRCimplementationinsideit.Itisnotpossibleto describetheoverallarchitecture,sincethissimulatoriscomposedbyaverylarge numberofblocks.ThelinklevelsimulatorisdesignedforthesimulationofMIMO-OFDMbasedwirelesscommunicationsystemslikeLTE/LTE-Aandrepresentsan effectivetoolfortheresearchanddevelopmentofinnovativephysicallayersystem components.Simulationsareobtainedaddinganindependentblock,theMMSE-IRCreceiver,into thephysicallayersimulator,developedusingCoCentricSystemStudio.MMSE-IRC block is intentionally implemented as a unique block, putting inside the corresponding functionalities,withtheobjectivetohaveaninterferercancellationreceiverthatcan beaccessibleandmodifiablequickly.ThedesignedMMSE-IRCisauniquesimulation block implemented in C language. ThemainimplementationconstraintforourMMSE-IRCisthelowcomplexity.Some techniquesareusedtoreducethecomputationburden:reducingthecomplexityof the matrix inversion, averaging and weighting coefficients computation.Interferingscenariosareselected,firstofall,totesttheMMSE-IRCcodeandafterto visualizetheperformanceintermsofRawBER,BLERandThroughputinpresenceof single or double interfering cells selecting different spatial correlations and DIPs. PerformanceresultsarecomparedwiththebaselinereceiverbasedontheAlamouti detectionscheme[ref.paperdiAlamouti],usingidealimplementationsdevelopedin MATLABandalsowiththemorerealisticsimulatorbasedonCoCentricSystem 41 Studio, showing how in the most cases MMSE-IRC provides a performance gain with respect to Alamouti. In the next chapter are also shown two other advanced receiver schemes that exploit theMMSE-IRCalgorithmandarebasedonthesymbollevelinterferercancellation (SLIC) and bit level interferer cancellation (BLIC) concept, comparing them and showing interestingfeaturesinordertodevelopanadaptivereceiverthatisabletoswitchor adapttheinterferencecancellationalgorithmasafunctionofthechanneland interference conditions. 3.1 General Architecture of the MIMO OFDMA simulator The general architecture of an MIMO OFDMA based system like LTE/LTE-A is described by the block diagrams in the figure below.Themodels(blocks)describedinthisdocumentarehighlightedingreencolor.The correspondinginputdatafiles(datasets)thatallowthemtobeconfiguredaccording to a specific standard are also shown, with the relation they have with each block. The same data set can be used by different functional blocks; this was intended in order to reduce as much as possible the number of data sets. Thedesignofthereconfigurablesimulationmodelswasdonewiththeaimofhaving blocks as flexible as possible and the source code in the CoCentric simulation platform as simple as possible, based on the use of the provided input data files (data sets). In thissense,thecomplexityofthefunctionsperformedbytheseblocksisimplicitin the data sets. 42 Figure 2: MIMO OFDMA system architecture 43 3.1.1 Data region Mapping/Demapping Theexplanationwillbeconcentratedinthemappingblock.Thedemappingblock basicallyperformstheinverseoperations,sojustthemostimportantdifferenceswill be pointed out. Figure 3: Data regions mapping block Thebasicresourceunitisastructureconstitutedbylogicalsubcarriers,with rectangular dimensionsdefinedbytheparametersBRU_freq_sizeandBRU_time_size,givenin numberofsubcarriersandOFDMAsymbols,respectively.Thenumberingofthe subcarriers inside the BRU is shown in the Figure 3. Not necessarily all the subcarriers are filled with data, being possible to reserve some subcarriers for other purposes. For 44 example, in the LTE system, the BRU (in this case calledResource Elements) has some positions reserved for the pilot subcarriers. For this reason, to describe the internalstructureoftheBRU,itisdefinedadatasetcontainingtheindexesofthe subcarriers that can be used for data transmission. By means of this data set, it is also determined thefilling order of thestructure,suchas frequency-first, time-firstorany other order, depending on the order the subcarriers indexes are listed. Figure 4: Basic Resource Unit (BRU) structure Thegenericresourcegrid(GRG)representsalltheallocableresourceswithina time/frequencyzone,beingconstitutedbyBRUs.Itisimportanttoremarkthatall BRUswithinaGRGmusthavethesamestructureandfillingorder,aspreviously explained.TheGRGhasrectangulardimensionsdefinedbytheparameters GRG_freq_size and GRG_time_size, given in number of BRUs in frequency and in time, respectively.ThenumberingoftheBRUsinsidetheGRGisshowninFigure4. Regarding the implementation of the block, it is also useful to view the GRG in terms of subcarriers, with the correspondent dimensions and numbering shown in Figure 5. 45 Figure 5: Generic Resources Grid (GRG) TheBRUsinsidetheGRGareallocatedbythespecificationofGDRs,aswillbe explainedinthefollowing.BRUsnotallocatedhavealltheirsubcarriersfilledwith zeroes. Figure 6: Resources Grid 3.1.2 Subcarrier Mapping/Demapping Thepurposeofthemappingblockistomapthesymbolsofdifferenttypes(data, pilots,othersignals)thatarriveorganizedinalogicalmanner(logicallyindexed),into theirscorrespondentphysicalresources,givenamappingrule.Aphysicalresourceis defined as a physical subcarrier (i.e., a given position in the IFFT/FFT) at a given time (in terms of OFDMA symbol offset). The physical resources are positioned over a grid with 46 dimensionsNFFTxNsymb.NFFTistheIFFT/FFTsizeandNsymbcorrespondstothe maximumbetweenthepilotspatternrepetitionperiodandtheextensionintime wherethemappingruleapplies(i.e.,themaximumoffsetintimebetweenalogical indexanditscorrespondentphysicalindex).Thenumberingofthephysicalresources in the grid is done as shown in the Figure 6. In general, a logically indexed subcarrier at the input can be mapped into any physical resource in the grid. Figure 7: Physical resources grid for subcarrier mapping Besides NFFT and Nsymb, other additional parameters shall be provided to the model: -Ndata: total number of data subcarriers in the grid, also equivalent to the rate of the data input port; -Npilot: total number of pilot subcarriers in the grid, also equivalent to the rate of the pilots input port; -Nnull:totalnumberofnullsubcarriersinthegrid,includingguard,DC,and other null subcarriers (when using MIMO, for example); -Nother: total number of subcarriers in the grid dedicated to other signals, such as synchronization signals or control channels in LTE. 3.1.3 IFFT/FFT calculation and cyclic prefix insertion/removal Intransmission,theGenericIFFT&CyclicPrefixInsertionmodel,asitsnamealready states, performs the IFFT calculation of the spectrum defined by the input subcarriers. 47 TheFFTsizedependsonthechannelbandwidthbeingconsidered.Insequence,the cyclicprefixisinsertedtakingacopyofagivennumberofsamples(CyclicPrefix length)attheendoftheusefulOFDMsymbol(justaftertheIFFTcalculation)and inserting them before it. Figure 8: IFFT and Cyclic Prefix insertion block Inreception,consideringthatthesystemisideallysynchronizedandthattime windowingisnot performed over theOFDMAsymbol, theGenericFFT&CyclicPrefix Removal model performs the inverse operations done in transmission. First, it removes thebeginningoftheOFDMAsymbolcorrespondingtothecyclicprefix.Finally,it performs the FFT calculation of the useful OFDM symbol. Figure 9: FFT and Cyclic Prefix removal block 3.1.4 Pilots compensation The purpose of the generic pilots compensation model is to compensate the received pilotstoremovethepowerboostandthespecificpilotsequence,basedonthe knowledge of the transmitted (reference) pilot sequence. After doing that, the value of eachpilotsymbolrepresentsanestimateofthechannelseenbythepilotsubcarrier itself. 48 Theblockoperatesoverthesamegridofthesubcarriersmapping(seetheFigure3), therefore using the same parameters and data sets (just the necessary ones) to know the location of the pilots subcarriers. 3.1.5 Channel Estimation Thepurposeofthegenericchannelestimationblockistoestimatethechannel coefficientscorrespondenttothereceiveddatasymbols.Theseestimatedvaluesare used in the subsequent blocks of the chain to perform some data processing over the datasymbols.Thechannelestimationisbasedonthereceivedpilotsubcarriersthat should be already compensated prior to enter in the block to remove power boost and the specific pilot sequence. Theestimationofthechannelcoefficientsisperformedusinglinearinterpolation, linear extrapolationandtheholdoperation(whichisindeedaparticularcaseoflinear extrapolation). Figure 10: Channel estimation block 49 Firstofall,itisdefinedaninterpolationgrid,withfrequencylengthequaltothe IFFT/FFTsizeandtimedurationNsymb,equaltotheperiodicityoftheinterpolation rules.TheparameterNsymbisnotnecessarilythesamedefinedinthegeneric subcarriers mapping model. The contents of the grid are the channel estimates of the correspondent subcarriers. An interpolation rule is a linear operation involving 3 points in the grid, where the channel estimate of adestination subcarrier is obtained from theknownestimatesofthetwosourcesubcarriers,consideringthe3pointsare positioned over a straight line. Therefore, it is possible to calculate the channel estimate related to a given subcarrier (destination), providing the channel estimates of the two source subcarriers and the proper weights. The weights are a function of the subcarriers indexes and can be pre-calculated for every defined interpolation rule. This information is then provided to the block by the data sets shown in the Figure 9, which contain all the interpolation rules (meaning first operand indexes and weights, second operand indexes and weights, and destinationindexes)tobeperformedinthegrid.Thechannelestimationisdonein steps, starting from the step 0, where at the beginning just the received pilot symbols are known. The pilots are assumed to be already compensated to remove sequenceandpowerboost.Astepincludesalltheinterpolationrulesthatcanbe defined using all channel estimates known at the end of the previous step. New steps should be included until all the required channel estimates are obtained. 50 Figure 11: Interpolation rules 3.1.6 Space-time Encoder/Decoder Thepurposeofusingthetechniqueofspace-timecodinganddecodingistosupport MultipleInputMultipleOutput(MIMO)antennasystemsinordertoalsoexploitthe spatial dimension. As consequence, an improvement in the capacity (throughput) or in the reliability (coverage range) of a wireless communication system can be obtained. Figure 12: Space-time encoder (MIMO 2x2) Two possible transmission modes of MIMO systems, the spatial multiplexing (SM) and thespace-frequencyblockcoding(SFBC).Thespatialmultiplexingisbasedonthe transmission of different data streams across the different transmitting antennas with 51 thegoalofincreasingtheoverallthroughput,whilethespace-frequencycoding techniques transmit redundant data streams over the multiple antennas for increasing the link reliability and extending the coverage range. 3.2 Modeling MMSE-IRC BeforeimplementingasimulationmodelinCcodeandcreatingablockinCoCentric withtheassociatedports,itisveryimportanttoprovideamathematicalexplanation oftheMMSE-IRCreceiver.Itisusefulto realize howcomplexitycan be managedand the importance of adapting our mathematical model to a real implementation. 3.2.1 MMSE-IRC for SFBC transmit diversity MMSE-IRCreceiverisbasedontheMMSEcriteria,buttheinterferencerejection combiningrequirehighlyaccuratechannelestimationandcovariancematrix estimation that includes inter cell interference. In this scheme, the covariance matrix is usedinamodifiedversionthatprovideslowercomplexity,avoidingthe4x4matrix inversion (MIMO 2x2 SFBC), leading to a trivial 2x2 matrix inversion.Lets consider a scenario where there is an UE and some interfering cells, the received signal by UE antennas is:

where, considering a MIMO 2x2 SFBC transmit diversity, Y is the 4x1 matrix containing the received signals by UE,

is the channel response in frequency domain 4x2 matrix between the serving cell and the UE,

is the transmitted useful signals 2x1 matrix, I is the total interference received 4x1 matrix, N is the 4x1 noise matrix. In a real context, the UE receives the summation of many signals plus noise composed by the useful signal (from the serving cell) and interferences (from interfering cells): 52

where:

is the 4x2 channel frequency response matrix between the c-th cell and the UE,

is the 2x1transmittedsignalmatrixandisthe4x1noisematrix, isthe serving cell and the other

cells are interferer cells. Thismatrixformulationcanbeextended,consideringtheSFBCtransmitdiversityin a 2x2MIMOfashion.WhenSFBCisenabled,consideringtwoantennasintransmission andtwoinreception(2x2MIMO),thetransmittedsymbolsareAlamouticoded exploitingtwoadjacentsubcarriersandthetwoantennas,sendingforeachtime instantfoursymbolsmappedinsubcarrierk(even)andk+1(odd).So,theprevious matrix equation can be expanded as: [

]

= [

]

[

][

]

The UE, implementing the MMSE-IRC, estimates the useful signal, in particular the 2x1 matrixcomposedbytwoestimatedservingcellsymbolstransmittedbythetwo antennas:

[

] Where,

is the estimated received symbol at the antenna 1 port and

is the sign inverted and conjugated estimated received symbol at the antenna 2 port. The

vector is obtained applying this relation:

53 where,

isthe2x4receiverweightmatrixcalculatedconsideringboth code and spatial domains. This matrix is generated considering the estimated channel matrix of the useful signal and the interferers plus noise covariance matrix.

can be calculated using one of the two following methods: 1th Method

where,

istheestimatedusefulchannelmatrixand

istheestimated interferences plus noise covariance matrix. From simulation tests, using this method it wasnotedthattheestimatereceivedsymbolhavetobenormalizedthroughthe followingnormalizing

function,consideringfortheantenna1portreceived symbol the matrix element

and for the antenna 2 port received symbol

:

so,

and

54 2nd Method

Inthiscase,thenormalizationprocessisnotnecessaryastheestimatedsymbolsare already normalized (i.e. the amplitude is correctly scaled for the subsequent symbol to bit demapping operation). Bothmethodsprovidethesameresult;thefirstoneisareducedcomplexitymethod becausethematrixinversionisdoneconsideringonlyoneoperand(

with eventuallyasplittingzero-addingoperation.Thesecondmethodcanbeusedwhen

does not contain zero values. Thecovariancematrix

includetheinterferencesandnoisecomponents,in general, it is defined as:

where I is the total interference received by the UE. It can be expressed neglecting the received useful signal (:

At the UE receiver, the total interference received by the UE on the subcarriers k and k+1 can be expressed as:

[

]

55 where

isthetotalreceivedinterferenceatantenna1portforthek-subcarrier,

is the total received interference at antenna 2 port for the (k+1)-subcarrier. Expanding

:

[

|

|

|

|

|

|

|

|

]

themaindiagonalrepresentsthereceivedinterfererpowersatantennaport1and port 2,theotherexpectationtermsarethecorrelationfunctionsbetweentheinterfering signals at antenna port 1 and port 2, the null terms are the auto-correlation function of theinterferencecalculatedovertwoadjacentsubcarriersthatcanbeassumedequal to zero. Besides,alsotheterms

,

],

,

are statistically zero and thus it is possible to avoid their estimation, so leading to the final matrix:

[

|

|

|

|

|

|

|

|

]

Obviously, the complexity is much lower in terms of matrix inversion, but the price to pay is a very small performance degradation.For simplicity, expectations can be expressed as:

[

]

56 The last matrix can be rewritten as:

[

] Consideringthat theinterferencecharacteristic changesslowlyintimeandfrequency domains, it possible to write:

So,

[

] Thisisanimportantapproximation,becausetocalculate

,itisonlyneedful knowing

anditstranspose.Now,calculating

isasimpleroperation, moreover in presence of zero matrix elements, the

4x4 matrix can viewed as the composition of two 2x2 matrix. In this case:

[

]

[

] The matrix inversion of

is simply:

[

] In the following, the relative sub-carrier indexes k and k+1 are omitted, considering: 57

Calculating the inverse matrix, it is possible to show the low complexity procedures:

[

] and,

[

] where

. Using, the first method for MMSE-IRC: [

]

[

] [

][

]

Imposingthat

,theestimatedreceivedsymbolattheUEantenna1port is:

The coefficients a, b, c and d are:

58 Moreover, the estimate received symbol at the UE antenna 2 port (

:

Itisimportanttonotethat,theabovevaluesarecomplexsymbols,sotheymustbe dividedinrealpartsandimaginaryparts, doing complexoperations.Extendingabove formulas,consideringcomplexvalues,therearenotimportantsimplifications,soitis not convenient splitting real part and imaginary part, but sometimes it is the only way to proceed. Fortunately, CoCentric is able to treat complex values and operations using a specific complex data format. So, in the following all the implemented variables are treated as complex values. 3.2.2 Building the MMSE-IRC receiver As already mentioned, the description of the main employed simulator blocks and the mathprocedure,isfundamentaltobuildanindependentblockthataccurately represents the MMSE-IRC receiver.Themathdescriptionappearsverysimple,becausetheapproximationsandcalculus aresimpletounderstandandtorealizeonpaper,butarealrealizationintoareal LTE/LTE-A simulator or in a real LTE/LTE-A chipset has to be done opportunely, solving several implementation problems, engineering some calculus to respect the LTE/LTE-A standard and the simulator software context. ChoosingtoimplementalltheoperationsinsidetheMMSE-IRCreceiver(e.g. covariance matrix estimation), the input and output ports are: INPUT PORTOUTPUT PORT float symbols_in1_I;float symbols_out_I; float symbols_in1_Q;float symbols_out_Q; 59 float symbols_in2_I;float reliability; float symbols_in2_Q; float reference_pilots_in1_I; float reference_pilots_in1_Q; float reference_pilots_in2_I; float reference_pilots_in2_Q; float h11_I; float h11_Q; float h12_I; float h12_Q; float h21_I; float h21_Q; float h22_I; float h22_Q; Table 10: Input/Output MMSE-IRC block data Moreoversomedatasetfileshavetobeloadedtoknowthepositionofusefuldata (e.g.pilotsubcarrierindexes).Inordertoestimatethecovariancematrix,itisvery importantknowexactlytheCRSpositions,somappingCRSindexesinadatafileitis possible to extract the interested data from a PRB.So,toestimatethecovariancematrix

,itisconsideredthattheestimationof thetotalreceivedinterfererisobtainedsubtractingtheestimatedreceivedsignalto the total received signal, for each OFDM symbol and subcarrier that belong to the CRS resource elements:

[

]

where,

is the 2x2 estimated covariance matrix,

is the CRS sequence of the serving cell at k-th subcarrier and l-th OFDM symbol, is the received symbol 60 by UE at k-th subcarrier and l-th OFDM symbol,

is the estimate channel response of the serving cell,

is the number of averaged samples. The average operation can be done considering a sliding windows to select the number ofPRBandsothenumberofCRSinsidetheslidingwindows.TheparameterK establishes the size of the sliding window: for example, if K=1 the estimated covariance matrix,theinterfererpowerattheUEantenna1andtheinterfererpowerattheUE antenna 2 are calculated for each PRB. ThefollowingC-codeshowstheimplementationoftheslidingwindowandthe estimations of covariance matrix and interferer powers at the UE antenna 1 and 2: for(i = 0; i < Nsymb*NFFT; i++) { for(i = 1; i = DC_POSITION) idx_low++;/* Skip DC */ if(idx_high >= DC_POSITION) idx_high++; /* Vector with the pilot indexes within the sliding window */ m = 0; x = 0; for(n=0; n= idx_low && j = idx_low && f