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