A study of precoding for LTE TDD using cellspecific reference signals

Fan Sun1, Muhammad Imadur Rahman2, David Astely21Radio Access Technology Section, Department of Electronic Systems, Aalborg University, Aalborg, Denmark;

2Radio Access Technologies, Ericsson Research, Kista, Swedene-mail: fs@es.aau.dk; muhammad.imadur.rahman@ericsson.com; david.astely@ericsson.com

Abstract We investigate non-codebook-based multiple-inputmultiple-output (MIMO) precoding schemes for the time divisionduplex (TDD) mode of LTE where channel reciprocity couldbe exploited. Previously proposed non-codebook-based precodingschemes typically use UE specific reference signals for demodula-tion. Cell specific reference signals are however still transmittedfor the transmission of common control signaling, mobilitymeasurements and downlink channel quality measurements. Inorder to save the resources occupied by UE specific referencesignals, and to simplify UE implementation, a non-codebook-based precoding scheme using cell-specific reference signalsis considered. Link throughput simulations indicate that suchscheme outperforms the scheme using UE specific referencesignals in the scenario with high transmit antenna correlationand low UE velocity.

Index Terms MIMO precoding, LTE, TDD, cell specificreference signals

I. INTRODUCTIONMulti-antenna techniques can significantly increase the data

rates and reliability of a wireless communication system. Theperformance is in particular improved if both the transmit-ter and the receiver are equipped with multiple antennas,which results in a multiple-input multiple-output (MIMO)communication channel. A core component in the 3GPP-LTE (3GPP-Long Term Evolution) standard is the support ofMIMO antenna deployments and MIMO related techniques.One of the features in LTE Release-8 is the support of aspatial multiplexing scheme with possibly channel dependentprecoding. MIMO precoding is one of the techniques toincrease system throughput performance [1], [2].

LTE allows for both codebook based and non-codebookbased precoding [3]. In the codebook-based precoding case, aset of precoder candidates is pre-defined at both the eNodeBand the User Equipment (UE) sides. The precoder is selectedfrom the codebook by the UE and the index of the selectedprecoder is fed back to the eNodeB, which may use thisprecoder for transmission. This scheme could be used for bothFDD and TDD [1], [4]. In addition to the codebook-basedbeamforming, LTE also supports more general codebook-freebeamforming. In this case, the eNodeB is not constrained toselect precoding vectors or matrices from a certain limitedset, and can exploit channel reciprocity to adjust the downlinktransmission weights from channel estimates obtained from

This work was performed when Fan Sun was with Radio Access Technolo-gies, Ericsson Research, Kista, Sweden.

uplink transmissions. In the general case, this is applicablefor both FDD and TDD. For FDD however the instantaneouschannel in uplink and downlink are typically uncorrelatedand only long term statistical properties such as a timeaveraged covariance matrix or direction of arrival can be used.For TDD however, since uplink and downlink occur at thesame frequency, short-term precoding based on instantaneouschannel knowledge can be considered [5].

In LTE Release-8, downlink transmission using UE specificreference signals, in here referred to as dedicated referencesignals (DRS), is supported for both FDD and TDD. WithDRS, codebook-free precoding can be implemented at thetransmitter. Since the individual antennas of the transmitter arenot visible to the UE and in contrast to the case with codebook-based precoding, arbitrary number of transmit antennas (e.g.more than four antennas as of Release-8) at the eNodeB canbe used. However, cell specific reference signals (CRS) arealways transmitted since they are required by the UEs in thecell for demodulation of the control signaling, for mobilitymeasurements as well as for channel quality measurementsfor link adaptation and scheduling.

In this paper, we consider codebook-free precoding usingCRS for demodulation. This enables potential overhead savingand does not require the UE to support channel estimationfor demodulation using DRS. Previously for WCDMA andcdma2000 systems, downlink beamforming using commonpilots (similar to CRS in LTE system) has been studied [6], [7],where the beams for data transmission are adapted to matchthe common pilot beam.

The main goal of this work is to study the possibility ofusing CRS for codebook-free precoding in TD-LTE systems,compared to codebook-free precoding using DRS for demod-ulation. Thus, we concentrate on comparison of codebook-freeprecoding using CRS compared to using DRS in this work.

The rest of this paper is organized as follows. In Sec-tion II, we describe the system model. The codebook-freeprecoding scheme employing DRS is presented in Section III.Section IV provides the details of the algorithm derivationfor the codebook-free precoding scheme employing CRS. Theinvestigation setup and the results are presented in Section V.Conclusions and some future work are presented in Section VI.

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II. SYSTEM MODEL

We will use the following notations. j =1, E[] is the

expectation computation, Ea[] is the expectation computationwith respect to vector a, ()H and ()T denote the Hermitiantranspose and the transpose of a vector or matrix, I denotesthe identity matrix, {} and {} stand for the real part andthe imaginary part of a complex value respectively, |a| standsfor the absolute value of a, and ||a|| is the norm of the vectora.

A. Downlink Reference SignalsIn a wireless communication system using coherent de-

modulation, reference signals are needed so that the receivercan compensate for the effect of the channel between thetransmitter and the receiver. In LTE downlink [1], both CRSand DRS are defined 1.

1) CRS are used for CQI measurement, mobility measure-ments as well as for demodulation of control signaling.There are up to four CRS patterns corresponding toantenna port from 0 to 3. The first two ports areshown in Figure 1. The CRS patterns on diverse antennaports are orthogonal to each other. CRS transmission isillustrated in Figure 2. For CRS-based downlink channelestimation, filtering and averaging are possible both inthe time domain as well as in the frequency domainsince the CRS are transmitted over the entire bandwidthin all downlink subframes.

0l

0R

0R

0R

0R

6l 0l

0R

0R

0R

0R

6l

One

ante

nna

port

Tw

oan

tenn

apo

rts

Not used for transmission on this antenna port

Reference symbols on this antenna port

0l

0R

0R

0R

0R

6l 0l

0R

0R

0R

0R

6l 0l

1R

1R

1R

1R

6l 0l

1R

1R

1R

1R

6l

PDCCH PDSCH

PDCCH PDSCH PDCCH PDSCH

Fig. 1. Multiple downlink CRSs for LTE.

2) DRS, can be used for the terminal to estimate the effec-tive channel, experienced by the data signal. DRS are to

1For more information, please refer to [1, Chapter 16].

Channelencoder

Datamodulation

MUX

MUX

Antenna weightDedicated reference signals (DRS)

Shared datachannel

Common reference signalsL1/L2 control signal

Br no.1

Br no.2

Br no.Ntx(Ntx=2,4 or 8)

Fig. 2. CRS and DRS Insertions for LTE.

be precoded together with data signal with the same pre-coder as illustrated in Figure 2. At the UE, the effectivechannel could be obtained via downlink channel estima-tion from DRS without the knowledge of the precoder.Only one DRS pattern is defined on antenna port 5 inRelease-8, and hence spatial multiplexing is not possible.The resource allocations on the time-frequency resourcegrid are displayed in Figure 3. DRS are allocated onthe resource blocks where the corresponding PhysicalDownlink Shared Channel (PDSCH) is mapped. ForDRS-based downlink channel estimation, the channelestimator can only use filtering and averaging within theresource block since the transmitter is allowed to changethe precoder with such frequency domain granularity.

0l 6l 0l 6l

R5

R5

R5

R5

R5

R5

R5

R5

R5

R5

R5

R5

PDSCHPDCCH

Fig. 3. Downlink DRS for LTE.

On the two-dimension time-frequency resource grid, thereare in total 168 resource units. The first one, two or three Or-thogonal Frequency Division Multiplexing (OFDM) symbolsare used to transmit control information in every downlinksubframe. For the case with three symbols for control signal-ing, we thus have 132 resource units in the remaining elevenOFDM symbols which can be allocated for data transmissionexcept for the DRS and CRS overheads. Hence, if employ-ing one CRS pattern (one antenna port), the available datatransmission proportions for DRS-assisted and CRS-assistedcodebook-free precoding schemes are 132612168 =

114168 and

1326168 =

126168 , respectively.

B. Multiple Antenna Transceiver ModelWe consider a MIMO system model considering one

OFDM sub-carrier (see Figure 4) for single user and single

stream (rank-1) transmission. s is the symbol to be transmitted,w is the Ntx 1 precoder with Ntx being the number oftransmit antennas, and H is the Nrx Ntx MIMO channelmatrix with Nrx being the number of receive antennas. n isthe receiver Nrx 1 additive noise and interference vector. Ina cellular system, it is not likely to be white. We for simplicitymodel it as spatially white in the following sections with eachindependent entry following CN (0, N0). gH is the 1 Nrxlinear equalizer.

w H

n

gHs x

+y s

Fig. 4. MIMO System Model.

Baseband transmission is simply expressed as

y = Hws + n, (1)and the detected symbol is denoted as

s = gHy = gH(Hws + n). (2)C. Spatial Correlation Model

The spatial correlation matrices for the transmitter and thereceiver are denoted as Rtx and Rrx, respectively. We assumethat the fading is spatially uncorrelated at the UE and onlyconsider Rtx of size Ntx Ntx.

It is approximated that diverse sub-rays transmitted fromthe antennas at the eNodeB have a small angle differenceand all clusters in the system give rise to the same angularspread. From [8], the angle is assumed to follow the Laplacedistribution, L(0, 2 ). In the situation with two transmitantennas, 0 = 20o, = 8o and 0 = 20o, = 46o areused to produce

Rtx =

[1 0.4455 0.8093j

0.4455 + 0.8093j 1

](3)

and

Rtx =

[1 0.0280 0.3069j

0.0280 + 0.3069j 1

](4)

in the high and low correlation scenarios, respectively. De-tailed derivations can be found in [9].

III. CODEBOOK-FREE PRECODING USING DRSIn this part, the codebook-free precoding design using DRS

is illustrated. Since DRS are multiplied with the same precoderas for data transmission, the equivalent channel estimate canbe directly obtained at the UE to demodulate data without theknowledge of precoder. The equalizer can be formed from thedownlink DRS channel estimate

gH = (Hw + nw)H, (5)where nw is the channel estimation error vector.

By exploiting channel reciprocity in the TDD mode, theprecoder is computed from the available Channel State In-formation at the Transmitter (CSIT). Instantaneous Signal-to-Noise Ratio (SNR) maximization is chosen as the de-sign criterion, which is related to Symbol Error Rate (SER)minimization. According to [10], for nearly all modulationschemes, the SER is expressed as

SER = E[ Q(2 SNR)], (6)

where Q() stands for the Q-Function, both and areparameters decided by the modulation type, and SNR is theinstantaneous SNR after equalization. From Eq. (2) and (5),

s = gHHws + gHn. (7)The instantaneous SNR, SNR conditioned on H, is formed as

SNR = Enw

[Es[(gHHws)(gHHws)H]En[(gHn)(gHn)H]

]

=P

N0Enw

[wHHHggHHw

gHg

],

(8)

where Es[ss] = P and En[nnH] = N0I. Under perfect Chan-nel State Information at the Receiver (CSIR) assumption, g =Hw, the instantaneous SNR maximization criterion is chosen.The constraint optimization problem with a per-antenna powercontrol requirement, indicating that every component in theprecoder should be smaller than a threshold, is formulated as

w = argmaxw

[wHHHHw

]s.t. |wi| 1

Ntx, i = 1, ..., Ntx.

(9)

Eq. (9) is a non-convex optimization problem [11], whereglobal optimum is hard to obtain within reasonable compu-tation time. With a total power constraint wHw = 1 asa relaxation, the precoder is explicitly the singular-vectorcorresponding to the largest singular value of HHH [12]. Thedesign heavily depends on the CSIT availability [13].

Algorithm 1: Equal Power Allocation (DRS)Step 1: SNR maximization (total power control)

w = argmaxw

[wHHHHw

]s.t. wHw = 1

w : singular vector of [HHH]

Step 2: Per-antenna equal power controlfor i = 1, ..., Ntx do

wi =wi

Ntx|wi|end for

One suboptimal solution is denoted as equal power al-location (DRS), given in Algorithm 1. In this method, weoptimize the objective function with wHw = 1 first. Then thecomponents are scaled in the precoder to guarantee |wi| =

1Ntx

, i = 1, ..., Ntx.The equal power allocation (DRS) method is equivalent

to the optimum with equal power control (DRS) approach in

the situation with two transmit antennas. In this approach,the precoder is first parameterized as [ 1

2ej2]T. Then the

optimization target is to find to maximize wHHHHw.

Optimum with equal power control (DRS)w = argmax

w

[wHHHHw

]s.t. |wi| = 1

Ntx, i = 1, ..., Ntx

IV. CODEBOOK-FREE PRECODING USING CRSIn this section, we present our design of the codebook-free

precoding scheme employing one CRS pattern (one antennaport).A. Precoder Design

Recall the MIMO system model in Figure 4, the equalizercan be reformed from the downlink channel estimate obtainedfrom one CRS pattern. A vector wp denotes the Ntx 1CRS weights for multiple physical antennas associated withone antenna port. Then (Hwp + np) is the downlink channelestimate from the single antenna port with np standing for thechannel estimation error vector. The equalizer is chosen as

gH = (Hwp + np)H. (10)The precoder design targets instantaneous SNR maximiza-

tion. From the detected symbol

s = gHHws + gHn, (11)the instantaneous SNR can be formed as

SNR = Enp

[Es[(gHHws)(gHHws)H]En[(gHn)(gHn)H]

]

=P

N0Enp

[wHHHggHHw

gHg

].

(12)

With perfect CSIR, g = Hwp. The SNR conditioned onH is

SNR =P

N0

wHHH(Hwp)(Hwp)HHw(Hwp)H(Hwp)

. (13)

To minimize Quadrature Amplitude Modulation (QAM)constellation rotation (cross-talk between the in-phase andthe quadrature components),

{(Hwp)HHw} > 0, {(Hwp)HHw} = 0 (14)are included as extra constraints.

Combining the optimization expression with the additionalconstraints including the per-antenna power and the con-stellation rotation minimization requirements, the constraintoptimization problem is formed as

w = argmaxw

[wHHH(Hwp)(Hwp)HHw

]s.t. |wi| 1

Ntx, i = 1, ..., Ntx

{(Hwp)HHw} > 0, {(Hwp)HHw} = 0.

(15)

Eq. (15) is also a non-convex problem. With the totalpower constraint wHw = 1 instead of the per-antenna powerrequirement, the precoder is

w =HHHwp||HHHwp|| .

(16)

Then we come at the suboptimal solution equal power allo-cation (CRS), shown in Algorithm 2. In the situation with twotransmit antennas, the equal power allocation (CRS) methodcoincides with the approach optimum with equal power control(CRS).

Algorithm 2: Equal Power Allocation (CRS)Step 1: SNR maximization (total power control)

w = argmaxw

[wHHH(Hwp)(Hwp)HHw

]s.t. wHw = 1,{(Hwp)HHw} > 0,{(Hwp)HHw} = 0

w = HHHwp

||HHHwp||

Step 2: Per-antenna equal power controlfor i = 1, ..., Ntx do

wi =wi

Ntx|wi|

end for

Optimum with equal power control (CRS)

w = argmaxw

[wHHH(Hwp)(Hwp)HHw

]s.t. |wi| = 1

Ntx, i = 1, ..., Ntx

{(Hwp)HHw} > 0, {(Hwp)HHw} = 0

B. Scaling Problem

The design criterion leads to mismatch between ||Hw|| and||Hwp||. Mismatch compensation is necessary to guaranteereliable QAM demodulation performance. For the situationwith two highly correlated transmit antennas, the distributionis estimated in Figure 5. In the following, it is assumed that theUE has only knowledge about the average of the distributionof ||Hw||||Hwp|| and uses it as a fixed compensation to form theequalizer. This is the same type of knowledge that is neededby the UE as for the case power boosting is used for the CRS.There are alternative approaches to avoid this problem at thetransmitter side and still have benefit of precoding on a systemlevel, but these are not further discussed in the present paper.

V. NUMERICAL EVALUATIONS

In this section, the codebook-free precoding schemes willbe evaluated in terms of link level throughput performancetaking into account the reference signal overhead.

0 0.5 1 1.5 2 2.5 30

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18probability density function

Fig. 5. ||Hw||||Hwp|| estimated distribution: Ntx = 2, high correlation.

TABLE ISYSTEM PARAMETERS

Carrier frequency 2.6 GHzSystem bandwidth 10 MHz

Number of sub-carriers 600Precoding granularity 5 RBAntenna configuration 2 Tx/2 Rx

Antenna calibration PerfectChannel model 3GPP Pedestrian A Model

Transmit antenna spatial correlation High correlationLow correlationUplink and downlink time difference 4 ms

UE speed 3 km/h or 30 km/h

Modulation and coding schemes QPSK,16 QAM,64 QAM13

Turbo codecSynchronization IdealRe-transmission No

Downlink channel estimation PerfectCRS pattern OneCRS weights wp = [1 0]Tor [0 1]T

A. System Parameters

The system parameters are presented in Table I. Theassumptions are mainly 22 antenna configuration, perfect an-tenna calibration, rank-1 transmission, and no re-transmission.We set the CRS weights for multiple physical antennas asso-ciated with one antenna port to wp = [1 0]T or [0 1]T. Inthis paper, we make the assumption that the CSIT includesknowledge to both UE antennas.

Quadrature Phase-Shift Keying (QPSK), rate 13 Turbo cod-ing, highly correlated transmit antennas, 5 Resource Block(RB) precoding granularity with perfect CSIT and CSIR areused as default evaluation setups unless clearly specified. Theloss due to DRS allocation can be noticed in the maximumachieved throughput compared to precoding using CRS.

B. Antenna CorrelationFigure 6 shows the codebook-free scheme using CRS out-

performs the codebook-free scheme using DRS in the situationwith high transmit correlation. For the scheme with DRS, hightransmit antenna correlation decreases the available degreesof freedom and the diversity order. Meanwhile, according toFigure 5, high transmit correlation facilitates the compensationat the UE for the mismatch between ||Hw|| and ||Hwp||.However, the scheme with CRS is less efficient in the lowtransmit correlation scenario, because the compensation forthe mismatch between ||Hw|| and ||Hwp|| is not possiblewhen low spatial correlation is experienced across antennas.

12 10 8 6 4 2 0 2 4 60

0.5

1

1.5

2

2.5

3

3.5

4

4.5x 106

Es/No(dB)

Thro

ughp

ut (b

ps)

Noncodebook,QPSK,Precoding granularity=5 RB

DRS, high transmit correlationDRS, low transmit correlationCRS, high transmit correlationCRS, low transmit correlation

Fig. 6. Throughput results with high and low transmit correlations.

C. Modulation SchemesFigure 7 indicates the results from the three modulation

levels in the situation with high transmit correlation. For eachmodulation level, the scheme with CRS is preferable comparedto the scheme with DRS. Hence, the fixed mismatch com-pensation technique works for the high transmit correlationsituation.

D. CSIT Imperfection: Time VaryingThe time-varying factor in the channel model ordinates

from the Doppler delay, which depends on the speed of the UE.Different UE speeds are used to produce the results in Figure 8.The results show that the increase of the UE speed has amore severe impact on the codebook-free precoding usingCRS than the precoding with DRS in the sense of throughputdegradation. Thus, the scheme with CRS is more UE velocitydependent. This indicates that the scheme with CRS can beintended for the low UE velocity scenario.

VI. CONCLUSIONIn this paper, we have studied a codebook-free precoding

design using channel estimates from CRS. The design hasthe potential of saving DRS overhead and possibly benefits

15 10 5 0 5 10 150

2

4

6

8

10

12x 106

Es/No(dB)

Thro

ughp

ut (b

ps)

Noncodebook,Precoding granularity=5 RB

DRS,QPSKDRS,16QAMDRS,64QAMCRS,QPSKCRS,16QAMCRS,64QAM

Fig. 7. Throughput results for different modulation schemes.

12 10 8 6 4 2 0 2 4 60

0.5

1

1.5

2

2.5

3

3.5

4

4.5x 106

Es/No(dB)

Thro

ughp

ut (b

ps)

Noncodebook,QPSK,Precoding granularity=5 RB

DRSDRS,3km/hDRS,30km/hCRSCRS,3km/hCRS,30km/h

Fig. 8. Throughput results for different UE speeds.

from channel estimation from CRS, which can employ time-frequency domain interpolation. Using numerical evaluations,we show that CRS based codebook-free precoding is prefer-able in some scenarios, such as high transmit correlation andlow UE velocity situation, etc. It is understood that in thosescenarios, the DRS overhead can be saved and thus, totalsystem throughput could be improved.

To further investigate the potential of the CRS basedcodebook-free precoding in system context, the impacts of thedownlink channel estimation process and the link adaptation,the influences of the uplink channel sounding imperfectionand the calibration errors, etc, need to be studied. One canalso consider other precoding algorithms, possibly based onother optimization criteria. Further, system level evaluationsare also needed to see the impact on system performance.

REFERENCES[1] E. Dahlman, S. Parkvall, J. Skold, and P. Beming, 3G Evolution - HSPA

and LTE for Mobile Broadband, 2nd ed. Academic Press, 2008.

[2] H. Ekstrom, A. Furuskar, J. Karlsson, M. Meyer, S. Parkvall, J. Torsner,and M. Wahlqvist, Technical solutions for the 3G Long-Term Evolu-tion, IEEE Communications Magazine, vol. 44, no. 3, pp. 3845, Mar.2006.

[3] S. Parkvall and D. Astely, The Evolution of LTE towards IMT-Advanced, Journal of Communications, vol. 4, no. 3, pp. 146154,Apr. 2009.

[4] Z. Liu, X. Wang, and J. Huang, A codebook based precoding scheme for3GPP TDD systems, in Proceedings IEEE WICOM2008, Oct. 2008,pp. 14.

[5] S. Parkvall, E. Dahlman, A. Furuskar, Y. Jading, M. Olsson, S. Wanstedt,and K. Zangi, LTE-Advanced - Evolving LTE towards IMT-Advanced,in Proceedings IEEE VTC2008-Fall, Sep. 2008, pp. 15.

[6] K. Pedersen, P. Mogensen, and J. Ramiro-Moreno, Application andperformance of downlink beamforming techniques in UMTS, IEEECommunications Magazine, vol. 41, no. 10, pp. 134143, Oct. 2003.

[7] R. Soni, R. Buehrer, and R. Benning, Intelligent antenna system forcdma2000, IEEE Signal Processing Magazine, vol. 19, no. 4, pp. 5467, July 2002.

[8] K. Pedersen, P. Mogensen, and B. Fleury, Spatial channel character-istics in outdoor environments and their impact on BS antenna systemperformance, in Proceedings IEEE VTC1998, May 1998, pp. 719723.

[9] F. Sun, Non-codebook based precoding by exploiting channel reci-procity in LTE-TDD, Master of Science Thesis, Royal Institute ofTechnology, Stockholm, 2009.

[10] J. G. Proakis, Digital Communications, 4th ed. Singapore: McGrawHill, 2001.

[11] Z.-Q. Luo, N. Sidiropoulos, P. Tseng, and S. Zhang, ApproximationBounds for Quadratic Optimization with Homogeneous Quadratic Con-straints, SIAM Journal on Optimization, vol. 18, no. 1, pp. 128, Feb.2007.

[12] J. Anderssen, Array Gain and Capacity for Known Random Channelswith Multiple Element Arrays at Both Ends, IEEE Journal on SelectedAreas in Communications, vol. 18, no. 11, Nov. 2000.

[13] M. Vu and A. Paulraj, MIMO Wireless Linear Precoding, IEEE SignalProcessing Magazine, vol. 24, pp. 86 105, Sep. 2007.

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