mimo lte advanced

IEEE Communications Magazine • March 2013 1270163-6804/13/$25.00 © 2013 IEEE

INTRODUCTION

The recent explosion of smart phone users andever increasing demand for high-quality multi-media over wireless are fueling the deploymentof Long Term Evolution (LTE) mobile commu-nication systems [1, 2]. Initiated in 2004, theLTE standardization effort focuses on enhancingUniversal Terrestrial Radio Access (UTRA) andoptimizing the Third Generation PartnershipProject’s (3GPP’s) radio access architecture. Ini-tial design targets of the LTE were to have theaverage user throughput be about three timesthat of Release 6 high-speed downlink packetaccess’s (HSDPA’s) in the downlink (100 Mb/s)and about three times that of the HSUPA’s inthe uplink (50 Mb/s). Its initial release (Rel. 8),which has been the basis for the LTE standard,was finalized in December 2008, and a subse-quent release (Rel. 9) was frozen in December

2009. Standardization of the latest release (Rel.10), popularly called LTE-Advanced (LTE-A),was closed in June 2011, and LTE Rel-11 is cur-rently under development.

Among many features in the LTE-A, whichsupports up to 3 Gb/s throughput in downlink,the multiuser multiple-input-multiple-output(MU-MIMO) scheme has been identified as oneof the key enablers for achieving high spectralefficiency [3]. From both the theory and designperspectives, MU-MIMO systems have severalunique features distinct from single-user MIMO(SU-MIMO) systems. Although both systemsprovide spatial multiplexing gains that are effec-tive in improving the throughput, cell coverage,and reliability of mobile communication systems,the SU-MIMO systems are vulnerable in scenar-ios where the spatial multiplexing capability of asingle user’s channel is limited either due to sig-nal-to-interference-plus-noise ratio (SINR) orfading correlations among antenna elements orby the number of receive antennas at the userside. To make up for the shortcomings of SU-MIMO, early LTE standards (Rels. 8 and 9)defined a primitive form of the MU-MIMOmode. The operations of MU-MIMO are elabo-rated and enhanced in the LTE-A standard(Rel. 10). Our purpose in this article is to pro-vide an overview of the key features of MU-MIMO systems defined/adopted in the LTE andLTE-A standards.

KEY DISTINCTIONS BETWEEN MU-MIMO ANDSU-MIMO SYSTEMS

Information theory highlights some key aspectsof MU-MIMO systems over SU-MIMO systems.First, it is well known that when the channelmatrix is full rank, the capacity gain of SU-MIMO systems is scaled by min {M, N} at highsignal-to-noise ratio (SNR), where M and N arethe number of antennas at the transmitter andthe receiver, respectively. In typical cellular sys-tems, the number of receive antennas at the bat-tery powered user (user equipment; UE) is oftensmaller than the number of transmit antennas atthe base station (enhanced node-B; eNB), limit-

ABSTRACT

Recently, the mobile communication industryis moving rapidly toward Long Term Evolution,or LTE, systems. The leading carriers and ven-dors are committed to launching LTE service inthe near future; in fact, a number of major oper-ators such as Verizon have initiated LTE servicealready. LTE aims to provide improved servicequality over 3G systems in terms of throughput,spectral efficiency, latency, and peak data rate,and the MIMO technique is one of the keyenablers of the LTE system for achieving thesediverse goals. Among several operational modesof MIMO, multiuser MIMO (MU-MIMO), inwhich the base station transmits multiple streamsto multiple users, has received much attention asa way of achieving improvement in performance.From the initial release (Rel. 8) to the recentrelease (Rel. 10), so called LTE-Advanced, MU-MIMO techniques have evolved from their pre-mature form to a more elaborate version. In thisarticle, we provide an overview of design chal-lenges and the specific solutions for MU-MIMOsystems developed in the LTE-Advanced stan-dard.

TOPICS IN RADIO COMMUNICATIONS

Chaiman Lim, Korea University

Taesang Yoo, Qualcomm Incorporated

Bruno Clerckx, Imperial College, London

Byungju Lee and Byonghyo Shim, Korea University

Recent Trend of Multiuser MIMO inLTE-Advanced

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128 IEEE Communications Magazine • March 2013

ing the gain of SU-MIMO systems to the num-ber of antennas at the receiver. In contrast,under the assumption that the transmitter hasperfect channel state information at the trans-mitter (CSIT), the sum capacity of MU-MIMOis scaled by min {M, Nn}, where n is the numberof users multiplexed into the MU-MIMO trans-mission, so an M-fold increase in the sum ratecan be obtained as long as Nn is larger than M.

Second, it has been shown that SU-MIMOsystems are susceptible to the poor behavior ofpropagation channels such as a strong line ofsight (LOS) path or strong correlations amongantenna elements. In such cases, the effectiverank of the channel matrix decreases, and sodoes the capacity gain of SU-MIMO. On theother hand, with the additional degrees of free-dom introduced by the co-scheduling of multipleUE devices, MU-MIMO systems can be designedto be less sensitive to the poor behavior of thechannel matrix, allowing MU-MIMO systems toachieve the full multiplexing gain regardless ofthe effective rank of each individual user.

CHALLENGES OF MU-MIMO SYSTEMSFrom a theoretical perspective, one of the majorbenefits of MU-MIMO systems is the realizationof the full spatial multiplexing gain. SupportingMU-MIMO operations, however, requiresappropriate resource allocation, in particular,among users. The aim of the user allocation is tochoose a group of UE devicess that, when co-scheduled, maximizes a predefined performancemetric (e.g., the sum throughput). To achievethis objective, channel state information (CSI) ofUE should be fed back to the eNB. A practicalproblem related to the CSI feedback is the bal-ancing of the feedback accuracy and the uplinkresource consumption caused by the feedback.Since feeding back real numbered CSI wouldrequire an infinite number of bits, the CSI needsto be represented (e.g., via appropriate quantiza-tion) with a limited number of bits. Note thatwhile the accuracy of the CSI affects the SNRoffset but not the multiplexing gain in SU-MIMO systems, such is not the case for MU-MIMO systems. In fact, since MU-MIMOsystems are interference limited under the finite-rate feedback constraint, the level of feedback

accuracy directly affects the multiplexing gain ofthe MU-MIMO downlink [4]. Another importantproblem related to the CSI feedback is how todetermine channel quality information (CQI) tobe fed back. Unlike SU-MIMO systems, UE inMU-MIMO cannot accurately estimate its SINR,due to the lack of knowledge of eNB’s beamselections for co-scheduled UE devices. Suchknowledge is typically unavailable to the UE atthe time of CQI calculation, as it is a function ofthe eNB’s scheduling decision that will in turn bedependent on the UE’s CSI feedback.

In the rest of this article, we provide anoverview of MU-MIMO techniques adopted inLTE and LTE-A. In particular, we summarizefeatures of MU-MIMO and the rationale behindthem defined in Rel. 8/9 LTE. We also devote asection to MU-MIMO techniques adopted inLTE-A as well as the technical grounds behindeach decision. Finally, we conclude the article.Since the terminologies of LTE standards mightbe unfamiliar to the reader, we put a summaryof commonly used technical terms and theirmappings to LTE standards in Table 1.

MU-MIMO IN RELEASE 8/9 LTELTE Rel. 8 supports a primitive form of theMU-MIMO as a direct extension of its SU-MIMO closed-loop spatial multiplexing mode. Ina nutshell, the MU-MIMO in Rel. 8 LTEemploys a codebook-based precoding, whereineach UE device measures its spatial channelusing the common RS (CRS) broadcasted fromthe eNB, selects the rank-1 precoder that bestrepresents the channel from a predefined code-book set, and then feeds back the index (PMI)of the codebook as well as the resulting CQI tothe eNB via an uplink channel. The eNB collectsthe PMI and CQI reports from different UEdevices and performs user grouping onto thegiven time/frequency resource such that thepaired UE devices experience a minimum levelof inter-stream interference among themselves.It is important to note that as far as the feed-back is concerned, the UE does not differentiateMU-MIMO from SU-MIMO. That is, the CQIat the UE is computed based on the assumptionthat there is no inter-stream interference causedby concurrent transmission from the eNB to aco-scheduled user. Since the CQI generated inthis way would be a bit optimistic, the eNB mayneed to apply a backoff to the reported CQI tochoose a right modulation order and code ratefor the UE. On top of this, an additional 3 dBbackoff is required as the power needs to beshared by the two UE devices.

Release 8 MU-MIMO (a.k.a transmissionmode 5) does not define a dedicated pilot.Hence, the UE should rely on the CRS for chan-nel estimation and demodulation of data. As theCRS is un-precoded, the UE should explicitlyderive the precoded channel by multiplying theestimated channel with the precoding informa-tion separately signaled to the UE through acontrol channel. A drawback of this approach isthat the eNB’s choice of precoding matrix is con-fined to those defined in the codebook.1 Thislimitation is relaxed in Rel. 10, as discussed inthe next section.

1 In general, it may bebeneficial for the eNB tochoose a precoding matrixoutside of the predefinedcodebook, an approachalso known as non-code-book precoding. Forexample, the eNB maywant to use zero-forcingbeams computed byinverting the compositechannel matrix construct-ed by stacking the rank-1channel vectors corre-sponding to PMIs.

Table 1. The nomenclature of MU-MIMO related terminologies in the LTEstandard.

LTE standard MU-MIMO terminology

Reference signal (RS) Pilot signal

User equipment (UE) User terminal, mobile

Enhanced NodeB (eNB) Base station

Precoding matrix indicator (PMI) Precoding codebook index

Rank indication (RI) MIMO channel rank

Physical downlink shared channel (PDSCH) Downlink data channel

Physical downlink control channel (PDCCH) Downlink control channel


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IEEE Communications Magazine • March 2013 129

Release 8 MU-MIMO relies on a single wide-band PMI reporting per UE, representing theaverage channel direction over the entire systembandwidth. Such a lack of frequency-selectivePMI reporting essentially limits the usefulness ofMU-MIMO to cells with a highly correlated uni-form linear array (ULA) antenna configuration,in which UE devices typically experience rank-1channels with rather non-frequency-selectiveeigenbeam directions.

Also, in Rel. 8, the SU-MIMO and MU-MIMO modes are semi-statically switched.Although a dynamic switching between twomodes may in principle allow more flexibility inthe scheduling and increase multiuser diversity,the lack of MU-MIMO-specific CQI reportingand the limited precoding mechanism in Rel. 8diminish the benefit of dynamic switching. Infact, Rel. 8 MU-MIMO is seen as beneficial onlyin certain scenarios (i.e., for heavily loaded cellswith highly correlated ULA antennas). Consider-ing these factors and also design simplicity, semi-static switching was chosen in Rel. 8.

In addition to CRS-based transmissions, Rel.9 supports rank-2 transmissions (called duallayer beamforming) using the demodulation RS(DM-RS). Unlike the CRS, which is common toall users in a cell and hence cannot be precoded,the DM-RS is UE-specific, that is, dedicated toeach UE and precoded along with accompanyingdata. Note that when the pilot is precoded, theprecoder information does not need to be sepa-rately delivered to the UE. In this sense, the useof precoded DM-RS makes the operation of theeNB transparent to the UE and enables the useof non-codebook-based precoding. In the duallayer beamforming, an orthogonal cover code(OCC) of length two is used to differentiatepilots on two layers. In addition, by defining twoscrambling IDs, the Rel-9 dual layer beamform-ing can support up to four-stream multiplexing,wherein the two groups are differentiated by dis-tinct scrambling IDs, and the two layers withineach group are separated by an OCC. Thisallows the eNB to schedule two UE devicessimultaneously in MU-MIMO mode, with twolayers assigned for each UE.2

MULTIUSER MIMO INLTE-ADVANCED

BRIEF OVERVIEWLTE-A systems should meet various require-ments of the International TelecommunicationUnion Radiocommunication StandardizationSector (ITU-R), including peak, average, andcell edge spectrum efficiencies [5]. Several newfeatures have been introduced in Rel. 10 toachieve these goals. First, in order to supporthigh-dimensional SU-MIMO operation (up to 8¥ 8 MIMO) and also improve MU-MIMO oper-ation, new RSs have been introduced in thedownlink. There are three different kinds of RSs— CRS, DM-RS, and channel state information(CSI)-RS. The CRS is used for CSI measure-ments and demodulation in legacy (Rels. 8 and9) transmission modes, as well as for controlchannel decoding, and various measurementsand UE procedures. The DM-RS, introduced in

Rel. 9, is extended in Rel. 10 to support up torank 8 transmissions in new transmission modes.The CSI-RS, newly introduced in Rel. 10, isused for CSI measurements in the new transmis-sion modes. Second, dynamic switching betweenSU-MIMO and MU-MIMO is adopted. Withthe use of DM-RS, an eNB can flexibly switchthe MIMO operation mode of UE with no needto report the precoding information to the UE.This helps the eNB to promptly respond to thevariations in the channel and system conditionssuch as the traffic type and the number of UEdevices. Third, as an effort to reduce feedbackload, a dual codebook structure is adopted forthe 8Tx configuration, where one codebook tar-gets capturing wideband and long-term channelproperties, while the other is designed to capturefrequency-selective and/or short-term channelproperties.

REFERENCE SIGNAL DESIGNOver the past years, practical schemes achievinga fair amount of capacity yet requiring reason-able precoding cost have been suggested [6, 7].It is widely known that the gain of these tech-niques over unitary precoding is considerable.This gain, however, is guaranteed only when theaccuracy of the CSI feedback is high enough. Tomaintain a reasonable CSI estimation qualitywhile avoiding the excessive pilot overhead,instead of a simple extension of CRS, Rel. 10has adopted a separate DM-RS/CSI-RSapproach.

The main features of the reference scheme inRel. 10 are as follows:• CRS is defined for only up to four transmit

antennas to limit the pilot overhead.• In the new transmission mode of Rel. 10

(transmission mode [TM] 9), the DM-RS isused for data demodulation of up to rank 8.

• In TM 9, CSI measurements are performedusing the CSI-RS. The CSI-RS is definedfor up to eight transmit antennas but withmuch lower overhead compared to theCRS.

• In legacy transmission modes, which cansupport up to rank 4, channel estimationand CSI measurements are performed usingthe CRS.Note that the DM-RS is not appropriate for

CSI measurements as the DM-RS is precoded ina UE-specific manner. That is, the DM-RS ispresent only on time/frequency resources wherethe UE is scheduling data. CSI-RS, on the otherhand, is unprecoded and defined over the entiresystem bandwidth for the CSI measurement. Inorder to minimize overhead, CSI-RS is transmit-ted in a fraction of subframes (Fig. 1). This is incontrast to the CRS, which is used for bothdemodulation and CSI measurements, and there-fore needs to be transmitted every subframe.

Unlike CRS, the DM-RS needs to be trans-mitted only for the active spatial layers wheredata is present. Thus, the DM-RS is advanta-geous in terms of the pilot overhead if the rankof the data transmission is less than the numberof transmit antennas, which is typically the casein 8-Tx antenna deployments. In fact, the DM-RS patterns in Rel. 10 are optimized for eachrank to minimize the pilot overhead.

2 However, the DM-RSbetween two groups is onlyquasi-orthogonal.

To make up for the

shortcomings of

SU-MIMO, early LTE

standards (Rels. 8

and 9) defined a

primitive form of the

MU-MIMO mode.

The operations of

MU-MIMO are

elaborated and

enhanced in the

LTE-A standard

(Rel. 10).


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IEEE Communications Magazine • March 2013130

The DM-RS patterns for ranks 3–8 in Rel. 10are natural extensions of that for rank 2 in Rel.9 and are based on hybrid code-/frequency-divi-sion multiplexing; for ranks 1 and 2, the DM-RSpatterns for the first and second layers are multi-plexed by code-division multiplexing (CDM),while for ranks 3 and 4, DM-RS patterns for thefirst and second layers and for the third andfourth layers are multiplexed by frequency-divi-sion multiplexing (FDM). Hybrid CDM+FDMDM-RS patterns are adopted for ranks 5–8 withtwo CDM groups.

MU-MIMO DIMENSIONINGConsidering the trade-off between performanceand signaling overhead, Rel. 10 has made thefollowing decisions on the dimensioning of MU-MIMO systems:• No more than four UE devices are co-

scheduled.• No more than two layers are allocated per

UE.

• No more than four layers are transmitted intotal.Multiplexing four UE devices implies that

each device receives only a quarter of the totaltransmit power and that the devices are also sub-ject to substantial inter-user interference. Alloca-tion of four UE devices would be viable in asituation where the cell contains a large numberof UE devices with high SNRs, and the rate gaindue to the spatial multiplexing and multiuserdiversity outweighs the per-UE rate loss causedby the power splitting and increased interference.Since scheduling more than four UE devices inMU-MIMO results in overly complicatedscheduling and UE implementation, and further-more such a scenario is uncommon in realdeployments, this case will be rare in practice.

For example, four layers may be able to besupported in single-pole ULA systems, wherespatial separation between UE devices is easier.However, in a realistic deployment with dual-polarized arrays, it is very hard to control the

Figure 1. DM-RS and CSI-RS patterns.

CRS port #1,2

0

Port 7(1111)

Port 8(1-11-1)

Port 11(11-1-1)

Port 12(-1-111)

Port 9(1111)

Port 10(1-11-1)

Port 13(1-1-11)

Port 14(-111-1)

Layer 1/2/5/6

Rank 88 DM-RS ports

OCC (orthogonal cover code) mapping for DM-RS

Layer 3/4/7/8

(a)

(b)

7 OFDM symbol (0.5 ms)

1 RB (resource block)

Time

RE (resource element)

12 subcarrier

14 50 10 1 0 14 54 5 4 50 14 52 36 72 32 3 2 36 76 7 6 72 36

CRS port #3,4

DMRS(rel.9/10)

DMRS(rel.10)

DRS (dedicated RS, rel.8) port #5, if configured

PDCCH PDSCH

7

Unlike CRS, the DM-

RS needs to be

transmitted only for

the active spatial lay-

ers where data is

present. Thus, the

DM-RS is advanta-

geous in terms of

the pilot overhead if

the rank of the data

transmission is less

than the number of

transmit antennas,

which is typically the

case in 8 Tx antenna

deployments.


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MU-MIMO interference at the eNB with thefeedback mechanism defined in Rel. 10. Hence,for systems with dual-polarized arrays, the num-ber of co-scheduled users will be two for mostcases.

With a highly correlated ULA, the eNB maydirect two streams separately to two UE devicesand thereby obtain the spatial multiplexing bene-fits. This is particularly true in a highly loadedscenario where the increase in the spatial degreesof freedom can be achieved by multi-userscheduling. Hence, a rank-1 transmission per UEmay be the most common scenario for this case.The gain of having more than rank 1 is negligiblein ULA but beneficial in dual-polarized systems.For example, in dual-polarized 8-Tx deploy-ments, each polarization array can form a beamand direct a data stream to a UE device, result-ing in a rank-2 transmission per user.

TRANSPARANCY OF MU-MIMOIn transparent MU-MIMO mode, the UE canperform decoding with only its own control sig-nal information (e.g., its own rank and DM-RSport). In contrast, information on co-scheduledUE devices needs to be provided in the non-transparent MU-MIMO mode. The co-schedul-ing information includes the total rank and theDM-RS ports of co-scheduled UE devices. Keydistinctions between two modes and their impli-cations on the system design are as follows.

Scheduling flexibility: The transparent MU-MIMO allows for more flexible scheduling. Forexample, under the transparent MU-MIMO,resources (RBs) allocated for UE multiplexed inMU-MIMO do not need to be fully aligned; theeNB may allocate partially overlappingresources to the UE devices and may even mul-tiplex different numbers of users on differentRBs. Also, DM-RS ports of co-scheduled UEcan be determined more dynamically for eachRB. On the other hand, under the non-transpar-ent MU-MIMO, the eNB may have to alignresource allocations of co-scheduled UE devicesso that a single signaling of the total rank andthe DM-RS ports of co-scheduled UE devices is

possible. This limits the scheduler flexibility andmay compromise the performance of MU-MIMO systems.

Control-signaling overhead: While transpar-ent MU-MIMO requires no additional controlsignaling regarding co-scheduled UE devices,non-transparent MU-MIMO requires morePDCCH resources to support user multiplexingand an advanced receiver operation of the UE.In transparent MU-MIMO, UE may have toresort to blind detection techniques to useadvanced receiver algorithms. Also, UE com-plexity might be substantial to support func-tions such as modulation classification andenhanced channel estimation. However, if itsown DM-RS ports and co-scheduled DM-RSports are delivered to the UE, channel informa-tion for the desired layers and the interferinglayers can easily be estimated by the orthogonalDM-RS ports, and thereby an advanced receiv-er technique (e.g., interference rejection com-bining or nonlinear interference cancellation)can be employed. In summary, to maximizeperformance using the advanced receiver, infor-mation about DM-RS ports, number of co-scheduled UE devices, MCS (modulationcoding scheme), and rank of each UE deviceare recommended in the downlink control sig-nalings. Considering the limited budget forPDCCH, the increase in control informationoverhead is undesirable and may put a morestringent limit on the number of co-scheduledUE devices per subframe.

To address this issue, Rel. 11 is discussingenhanced PDCCH on the PDSCH region.

After weighing these pros and cons, Rel. 10has decided to support transparent MU-MIMO.Additional signalling issues will be discussed inthe upcoming releases.

SU/MU-MIMO DYNAMIC SWITCHINGWhile SU-MIMO systems improve the peak/average UE throughput by transmitting multiplestreams in the same time/frequency band, MU-MIMO systems provide higher peak/average sys-tem throughput by exploiting multiuser diversity.

Figure 2. SU/MU-MIMO dynamic switching.

MU-MIMO

DCI for dynamic switching

SU-MIMO

CQI/PMI/RI

DynamicswitchingbetweenSU/MU

eNBPacket data

K UEs index {1,2,⋅⋅⋅,K} MUEs

Scheduler

UE 1

UE 2

UE K

PrecodingW

To maximize

performance using

the advanced

receiver, information

about DM-RS ports,

number of

co-scheduled UEs,

MCS (modulation

coding scheme) and

rank of each UE are

recommended in the

downlink control

signalings.


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To get the maximal benefit of both, Rel. 10introduced dynamic switching between the SU-MIMO and MU-MIMO modes (Fig. 2). Themain feature of the dynamic switching is tochange the mode per subframe basis, based onthe channel condition and traffic.

In order to support SU/MU-MIMO dynam-ic switching, as well as the rank adaptation inthe SU-MIMO mode, information on DM-RSantenna ports and the number of layers shouldbe delivered to the UE. For this purpose, anew downlink control information (DCI) for-mat, DCI format 2C, has been defined. Asshown in Table 2, DCI format 2C containsantenna port information, the scrambling iden-tity (SCID) of the DM-RS, and the number oflayers. In LTE-A, the eNB can transmit up totwo codewords by spatially multiplexing theminto up to eight layers. The boldface entries inthe table indicate message formats for MU-MIMO, and the rest indicate those for SU-MIMO. The UE dimensioning and layerseparation of Rel. 10 MU-MIMO is the sameas that of Rel. 9 MU-MIMO discussed in theprevious section.

CSI FEEDBACK MECHANISMThere are a number of factors that have been orwill have to be considered in the design of thefeedback mechanism in Rel. 10 and futurereleases. First of all, backward compatibilityshould be guaranteed; Rel. 10 UE moving into aRel. 8/9 network should be able to be configuredto report feedback information (PMI, RI, andCQI) according to the Rel. 8/9 format for seam-less service. Likewise, PMI, RI, and CQI feed-back mechanisms need to be supported for Rel.8/9 UE in the Rel. 10 network.

Second, feedback overhead should be investi-gated carefully. Overall, there are two types offeedback mechanisms — explicit feedback andimplicit feedback. Explicit feedback refers to thedelivery of the channel matrix H and/or covari-ance matrix HHH from the UE to the eNB, while

implicit feedback indicates the mechanism of theRel. 8 feedback employing PMI, RI, and CQI.Considering its low feedback overhead, implicitfeedback has been selected in Rel. 10. Nonethe-less, since explicit feedback provides betterscheduling flexibility, this issue will continue tobe discussed in the future LTE-A releases.

Third, UE feedback design should take realdeployment scenarios into account. Note thatdevice space limitations do not allow a largespacing at the eNB, not to mention at the UE.One commonly used technique for reducing thephysical space is to employ dual-polarized anten-nas, where the antennas are grouped into pairsto form polarized collocated antennas.

In the standardization process, manyapproaches to improve the Rel. 8 implicit CSIfeedback mechanism have been proposed [8].We briefly describe key features of theseschemes.

Adaptive codebook: The eNB can apply thetransformed adaptive codebook on top of thefixed baseline codebook. UE may feed back anestimate of the correlation matrix or eigenvectorto the eNB on a long-term basis. Any codebookmay be used as the baseline codebook, so theRel. 8 codebook could also be reused for thisapproach.

Differential feedback: Differential feedbackenables the eNB to track channel variationbetween adjacent feedbacks efficiently. Initially,the UE feeds back a full CSI as a reference.Next, the UE feeds back the difference betweenthe previous CSI and the current one. The UEquantizes this difference using a differentialcodebook so that the index of the differentialcodebook is reported to the eNB. A well-knowndrawback of differential feedback is the sensitivi-ty to error propagation. Due to channel correla-tion between two adjacent channel blocks, thedifference can be delivered with improved accu-racy or lower overhead.

Multiple description coding (MDC): In everyPMI report, more than one PMI generated fromdifferent codebooks are provided to give differ-ent observations of the channel. By interpolatingdifferent observations, a more accurate estimateof the channel can be obtained. While the differ-ential codebook exploits temporal correlationbetween adjacent CSIs, such is not the case forMDC since the collection of the PMI from dis-tinct codebooks is used. Therefore, even if onePMI is dropped, the eNB can still estimate thechannel by using the rest.

Best/worst companion PMI: This approachperforms an additional feedback for better co-scheduling. Toward this end, both best and worstPMIs are delivered. Moreover, best companionreport includes a delta CQI representing theSNR loss induced by the addition of anotheruser on the same resource. Although additionaloverhead is relatively small, it is still non-negligi-ble, and the load of the scheduler to find thebest UE pairs is considerable.

Multirank PMI/CQI: This method reportsmultiple PMI/CQI pairs with different ranks. Eachfeedback corresponds to SU-MIMO with any rankor MU-MIMO with low rank. This multiple feed-back information expedites dynamic switchingbetween SU-MIMO and MU-MIMO.

Table 2. Antenna port(s), scrambling identity, and number of layers indication.

One codeword:Codeword 0 enabled,Codeword 1 disabled

Two codewords:Codeword 0 enabled,Codeword 1 enabled

Message Message

0 1 layer, port 7, SCID=0 0 2 layers, ports 7–8, SCID=0

1 1 layer, port 7, SCID=1 1 2 layers, ports 7–8, SCID=1

2 1 layer, port 8, SCID=0 2 3 layers, ports 7–9

3 1 layer, port 8, SCID=1 3 4 layers, ports 7–10

4 2 layers, ports 7–8 4 5 layers, ports 7–11



7 Reserved 7 8 layers, ports 7–14


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DUAL CODEBOOK OPERATION

Release 10 adopted the multigranular feedbackstructure referred to as dual-stage feedback [8].The precoder in dual-stage feedback consists oftwo matrices (W1 and W2), and each of thembelongs to a separate codebook. A compositeprecoder is the product of the two and given by[9]

W = W1W2, (1)

where W1 is in charge of wideband and long-term channel properties, and W2 captures fre-quency selectivity and short-term channel fading.A major advantage of decoupling the long-termand short-term CSI feedback components is lowfeedback overhead and improved performanceover the single codebook [10]. Below we providemajor principles behind the Rel. 10 codebookdesign. Readers are referred to [11] for moredetails.• The codebook design puts more emphasis

on lower ranks (ranks 1 and 2), where theprecoding gain is more pronounced.

• All entries in a precoding matrix need tohave the same magnitude (constant modu-lus) to relieve the burden on the poweramplifier design.

• Unitary precoding is preferred to maintaina constant average transmitted power.

• W1 (= [X 0; 0 X}]) should be block diago-nal since this structure is well matched tothe spatial covariance of the dual-polarizedantenna setup with any antenna spacing(e.g., l/2 or 4l)

• X is a 4 ¥ Nb matrix, where Nb is number ofbeams (1~4). For each N1, adjacent over-lapping beams are used to reduce the edgeeffect in the frequency-selective precoding.

• At least sixteen 8Tx discrete Fourier trans-form (DFT) vectors are generated fromW1, and a co-phasing via W2 is performedin order to match with the spatial covari-ance of the ULA antenna setup and to copewith the phase shift between polarizations.In Rel. 10, the dual codebook structure is

applied only on the 8Tx mode, and the 4Tx and2Tx modes still employ the legacy codebook(Rel.-8-based codebook). According to therecent study in Rel. 11, however, a dual code-book scheme is beneficial for a 4Tx case such ascross-polarized macro sites and outdoor smallcells with localized antennas [12].

In order to observe the gain of the Rel. 10

dual codebook, we compared the performanceof Rel. 8 and Rel. 10 codebooks.

In our simulation, we assume that each UEhas a single layer and sends the feedback infor-mation (RI, PMI, and CQI) to the eNB. Whenthe UE is requesting two ranks (2 PMI and 2CQI), therefore, the eNB regards it as twoindependent UE devices with a single layereach. Using all feedback information from theUE, the eNB performs the MU-MIMO opera-tion. In our simulations, the following cases areinvestigated:• Extended Rel. 8 codebook (CB): The UE

reports a 4-bit PMI. Since the codebook for8Tx is not defined in LTE Rel. 8, we insteaduse the rank-1 codebook of 802.16m(WiMAX) [13], which is a unitary codebookconsisting of 16 elements. Note that Rel. 8employs wideband PMI only in MU-MIMO,but we also test the subband PMI for thesake of comparison.

• Release 10 dual codebook: The UE reports4-bit wideband PMI W1 and 4-bit subbandPMI W2 [11].

• Adaptive codebook [14]: In this codebook,W1 is replaced by the channel covariance

Table 3. 8 ¥ 2 antenna configuration (XXXX Æ ÔÔ channels, 0.5 l antenna spacing, 8° angle spread).

ZFBF MU-MIMO 8 ¥ 2 with MAX 4 LAYERS Average cell spectralefficiency (b/s/Hz)

5 percent cell edgespectral efficiency(b/s/Hz)

Extended Rel. 8 codebook (4-bit wideband) 3.26 0.14

Extended Rel. 8 codebook (4-bit subband) 3.30 0.14

Rel. 10 dual codebook (W1 wideband + W2 subband) 4.38 0.21

Adaptive codebook (unquantized Rt, report every 500 ms) 4.70 0.22

Figure 3. Average UE throughput for various codebook schemes.

Average UE throughput (Mbp/)50

0.1

0

CD

F

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

10 15 20

Extended Rel. 8 CB (wideband)Extended Rel. 8 CB (subband)Rel. 10 dual CBAdaptive CB


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matrix Rt = E[HHH]. That is, adaptivecodebook consists of the long-term channelcovariance matrix Rt and W2. In order toobserve the best possible performance, weused unquantized matrix Rt.Once the codebook cn is determined, we per-

form zero-forcing beamforming (ZFBF) for eachscheme. Let N and K be the number of transmitantennas at the eNB and selected users, respec-tively; then the transmit signal after the linearprecoding becomes x = Wu where W is an N ¥K ZFBF precoding matrix, and u = {u1, …, uK)T

is the user symbol vector. Using the estimated channel matrix ^H = [^hT

1,..., ^̂hT

K]T where ^hk = cHn is the channel response

of the kth UE, W is computed as

(2)

where fk is the kth column of F and p = (p1, …,pK) is the vector of power normalization coeffi-cients

Detailed simulation assumptions are provid-ed in Table 4. In a real implementation, theeNB usually uses cross-polarization consideringspace limitation for 8Tx. On the other hand,because it is difficult to implement exact dual

= =W F p H HH Pdiag( ) ˆ ( ˆ ˆ ) diag( )H H1/2 1 1/2

=pP

K f

1k

k2

Table 4. System simulation assumptions.

Parameter Value

Duplex method FDD

Bandwidth 10 MHz

Network synchronization Synchronized

Cellular Layout Hexagonal grid, 19 cell sites, 3 sectors per site

Users per sector 10

Downlink transmission scheme 8 ¥ 2 MU-MIMO ZFBF with rank adaptation with 1 layer per UE

Downlink scheduler Proportional Fair scheduling in the frequency and time domain.

Downlink link adaptation

CQI and PMI 5ms feedback period1 PMI and 1 CQI feedback per subband (=4 consecutive RBs)6ms delay total (measurement in subframe n is used in subframe n+6)Unquantized CQI, PMI feedback error: 0%MCSs based on LTE transport formats [36.213]

Allocation localized

Downlink HARQ Maximum 3 retransmissions, IR, no error on ACK/NACK, 8 ms delaybetween retransmissions

Downlink receiver type MMSE based on DM RS of serving cell

Channel estimation Non-ideal channel estimation on CSI-RS and DM-RS vs. CINR curvesbased on LLS provided as an input to SLS.

Antenna configuration XXXX->ÔÔ channels, 0.5l antenna spacing, 8° angle spread

Control Channel overhead,Acknowledgements etc.

LTE: L = 3 symbols for DL CCHsOverhead of DM-RS: RANK 1, 2 : 12 REs/RB/subframeOverhead of CSI-RS: 4/8 sets of CSI-RS every 5 ms and 1RE/port/RB(This is, in the 8Tx antenna case, 8 REs/RB per 5 ms)Overhead of 2-port CRS

BS antenna downtilt Case 1 3GPP 3D: 15 degrees

Channel model SCM urban macro high/low spread for 3GPP case 1, 3 km/h

Intercell interference modeling 7 intercell interference links are explicitly considered.The remaining links are modeled with Rayleigh distribution.

Max. number of layers (UE) 4

While the differential

codebook exploits

temporal correlation

between adjacent

CSIs, such is not the

case for the MDC

since the collection

of the PMI from

distinct codebooks is

used. Therefore,

even if one PMI is

dropped, the eNB

can still estimate

the channel by

using the rest.


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polarized antennas in a terminal, UE employssingle polarization while maximizing antennaspacing within terminal with fixed area. In anutshell, we simulate an XXXX(eNB) ÆÔÔ(UE) configuration, where XXXX and ÔÔrefer to cross-polarization and single-polariza-tion, respectively. The simulation results aresummarized in Table 3 and Fig. 3. While achiev-ing performance close to the adaptive code-book, Rel. 10 dual codebook achieves 34.3percent gain on average and 50 percent gain inthe cell edge when compared to the extendedRel. 8 codebook.

Therefore, we conclude that Rel. 10 dualcodebook is a very competitive option in cross-polarized antenna setup.

CONCLUDING REMARKS ANDFUTURE DIRECTION

In this article, we have reviewed the main fea-tures of MU-MIMO techniques adopted in LTEand LTE-A standards. The major enhancementof the downlink MU-MIMO in Rel. 10 is thesupport of eight transmit antennas to allowsimultaneous transmission of up to eight layers.Such enhancement is made possible by the intro-duction of new measurement and demodulationreference signals enabling non-codebook-basedprecoding and a novel CSI feedback mechanismrelying on a high-performance and low-overheaddouble codebook structure.

Recently, standardization effort for LTERel. 11 has started, and the radio access net-work (RAN) working group is discussingenhancement of downlink MIMO as a studyitem. Given the importance of MU-MIMOoperation for network operators to meet theincreasing user demands of the fourth genera-tion (4G) and beyond 4G (B4G) wireless sys-tems, CSI feedback and control signaling willbe further improved in future release. Also, afuture release will pay particular attention toenhancing the MU-MIMO for realistic deploy-ment scenarios. For instance, enhancing theCSI feedback for 4Tx cross-polarized antennaarrays will be one priority. Moreover, giventhe recent deployment of heterogeneous net-works, there is a need in future releases toaccount for small cel l deployment whendesigning MU-MIMO. MU-MIMO systemswill continue to be improved to provide solu-tions for those issues.

ACKNOWLEDGMENTSThis work was supported by the KCC R&D pro-gram (KCA-12-911-01-110) and the NRF grantof MEST Korea (No. 2012R1A2A2A01047510).

REFERENCES[1] http://network4g.verizonwireless.com/#/4g-network-ver-

izon-wireless[2] E. Dahlman, S. Parkvall, and J. Skold, 4G LTE/LTE-Advanced

for Mobile Broadband, Academic Press, 2011.

[3] F. Boccardi et al., “Multiple-Antenna Techniques in LTE-Advanced,” IEEE Commun. Mag., vol. 50, no. 3, Mar.2012, pp. 114–21.

[4] T. Yoo, N. Jindal, and A. Goldsmith, “Finite-Rate Feed-back MIMO Broadcast Channels with a Large Numberof Users,” Proc. IEEE ISIT, July. 2006, pp. 1214–18.

[5] 3GPP TS 36.913, “Evolved Universal Terrestrial RadioAccess (E-UTRA); Requirements for further advance-ments for Evolved Universal Terrestrial Radio Access (E-UTRA) LTE-Advanced.”

[6] M. Sharif and B. Hassibi, “On the Capacity of MIMO Broad-cast Channels with Partial Side Infonnation,” IEEE Trans.Info.Theory, vol. 51, no. 2, Feb. 2005, pp. 506–22.

[7] T. Yoo and A. Goldsmith, “On the Optimality of Multi-Antenna Broadcast Scheduling Using Zero-ForcingBeamforming,” IEEE JSAC, vol. 24, no. 3, Mar. 2006,pp. 528–41.

[8] 3GPP TSG RAN WG1 #60, R1-101129, “On Extensionsto Rel-8 PMI Feedback,” Feb. 2010.

[9] 3GPP TSG RAN WG1 #61, R1-103332, “Way Forwardon UE Feedback,” May 2010.

[10] 3GPP TSG RAN WG1 #61, R1-103378, “PerformanceEvaluations of Rel.10 Feedback Framework,” May 2010.

[11] 3GPP TSG RAN WG1 #62, R1-105011, “Way Forwardon 8Tx Codebook for Rel.10 DL MIMO,” Aug. 2010.

[12] 3GPP TR 36.871 V11.0.0, “Evolved Universal TerrestrialRadio Access (E-UTRA); Downlink Multiple Input Multi-ple Output (MIMO) enhancement for LTE-Advanced(Release 11).”

[13] IEEE Std 802.16mTM-2011, “Amendment 3: AdvancedAir Interface,” May 2011, pp. 740.

[14] 3GPP TSG RAN WG1 #58, R1-093059, “Adaptive Feed-back: A New Perspective of the Adaptive Codebook,”Aug. 2009.

BIOGRAPHIESCHAIMAN LIM is currently working toward his Ph.D. degreein the School of Information and Communication, KoreaUniversity, Seoul. His research interests include communica-tions and information theory, signal processing for wirelesscommunications, and advanced MIMO systems.

TAESANG YOO received his B.S. degree (Hons.) in electricalengineering from Seoul National University, Korea, in 1998,and his M.S. and Ph.D. degrees in electrical engineeringfrom Stanford University, California, in 2003 and 2007.Since 2006, he has been with Corporate Research andDevelopment of Qualcomm, where he is currently workingon 3GPP LTE and LTE-Advanced wireless systems. Hisresearch interests include heterogeneous cellular networks,multiple-antenna systems, receiver algorithms, and variousdesign and performance aspects of LTE/LTE-A systems andstandards.

BRUNO CLERCKX received his Ph.D. degree from Universitecatholique de Louvain, Belgium. He held visiting researchpositions at Stanford University and EURECOM, and waswith Samsung Electronics from 2006 to 2011. He activelycontributed to 3GPP LTE/LTE-A and acted as Rapporteur forthe 3GPP CoMP Study Item. He is now a lecturer (assistantprofessor) at Imperial College London and an editor forIEEE Transactions on Communications.

BYUNGJU LEE received his B.S. degree from the School ofInformation and Communication, Korea University, in2008, where he is currently working toward his Ph.D.degree. His research interests include wireless communica-tions and network information theory.

BYONGHYO SHIM received B.S. and M.S. degrees in controland instrumentation engineering from Seoul National Uni-versity in 1995 and 1997, respectively, and an M.S. degreein mathematics and a Ph.D. degree in electrical and com-puter engineering from the University of Illinois at Urbana-Champaign in 2004 and 2005, respectively. From 2005 to2007, he worked for Qualcomm Incorporated. SinceSeptember 2007 he has been with the School of Informa-tion and Communication, Korea University, where he iscurrently an associate professor. His research interestsinclude wireless communications and information theory.

Given the recent

deployment of

heterogeneous

networks, there is a

need in future

releases to account

for small cell

deployment when

designing the

MU-MIMO.

MU-MIMO systems

will continue to be

improved to provide

solutions for

those issues.


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