201O International Conference on Information, Networking and Automation (ICINA)

Uplink Multi-user MIMO Interference Cancellation Algorithm for LTE-A Systems

Xiangyou Lv, Tiankui Zhang, Zhimin Zeng School of Information and Communication Engineering

Beijing University of Posts and Telecommunications Beijing 100876, China

02jordan@bupt.cn

Abstract - An uplink multi-user multi-input mUlti-output (MIMO) multiple access interference cancellation algorithm is proposed for Long Term Evolution-Advanced (L TE-A) system. The base station (BS) obtains the null space of pairing user's channel matrix by channel state information, and then this null space is constructed as the transformation matrix which maintains the multiplexing degree of spatial channel. The received signal at the BS is processed by the transformation matrix, and the multiple access interference of pairing user can be eliminated. Furthermore, during the resource scheduling, the user equipments (UEs) which use the same codebook are confined to occupy the same time-frequency resource. So the probability of UEs with strong channel correlation paired each other is reduced, and the impact of transformation matrix on useful signal strength can be minimized. Simulation results show that the proposed algorithm can depress the multiple access interference of pairing user greatly and increase the signal to interference-plus-noise ratio of the user, and eventually improve the system throughput.

Key words: LTE-A; multi-user MIMO; interference cancellation; matrix transformation

I. INTRODUCTION

Multiple antennas technique research is very important for next-generation wireless systems. Multiple-input multiple-output (MIMO) systems have been investigated a lot in LTE-A[I]. The capacity of a MIMO system with Nt transmitters and Nr receivers grows linearly with min (Nt, Nr) [21. Considering the effect of size and cost, the UE usually has two antennas in LTE-A systems, so the system capacity is limited. One of the solutions is multi-user MIMO (MU­MIMO), which means that the BS sends multi-stream data via multiple antennas on the same time-frequency resource to the different UE. MU-MIMO system experience co-channel interference, also referred to as multiple access interference (MAl) in uplink, as well as multi-user interference (MUI) in downlink. That is bottleneck which constrains MU-MIMO performance [31 [41.

Multi-user interference cancellation in downlink MU­MIMO system was investigated in two aspects: dirty paper coding (DPC) and linear zero forcing preprocess. DPC can obtain the maximum capacity gain [3116], however, are too complicated for cost-effective implementations. Linear zero forcing preprocess, for example block diagonalization (BD) [6][7][8][9f based on linear pre-coding and zero-forcing beam-

Li Wang China Academy of Telecommunication Research

the Ministry of Industry and Information technology Beijing 100037, China

forming (ZFBF), have a low complication. They were concerned with 3rd Generation Partnership (3GPP) and other international organizations.

As the CSI (Channel State Information) of all users can be obtained through pilot in downlink MU-MIMO system, BS can schedule user pair according to the channel quality of each user. Also the pre-coding matrix of each user can be designed to be null space of the pairing user's (user which occupancy the same time-spectrum resource with desired user) channel matrix, so that MU-MIMO channel can be decomposed to parallel SU-MIMO channel. And multi-user interference can be cancelled [7]. As UEs can't predict other user's CSI in uplink MU-MIMO, also 3GPP decided to use codebook based pre-coding in uplink [10], MAl cancellation can't be executed by preprocessing as downlink. In [9], BS obtain the null space of pairing user's channel matrix, and post-process the received signal as channel transformation to cancel the pairing user's MAL But the null space of pairing user's channel matrix can depress the multiplexing gain of spatial channel and deteriorate the useful signal intensity. [9] considers MAl cancellation only, doesn't evaluate the infection of null space to the useful signal intensity.

In this paper, considering the impact on the useful signal intensity as applying null space to cancel pairing user's MAl, null space is constructed to be the transformation matrix which can't depress the mUltiplexing gain of spatial channel and deteriorate the useful signal intensity. Based on the matrix transformation, scheduling of pairing user was restricted according to the codebook selected, to minimize the affection to the desired user's signal intensity further.

II. MU-MIMO SYSTEM MODEL

Figure 1. Schematic of an uplink MU-MIMO system

The schematic of the uplink (UL) MU-MIMO system considered in this paper is shown in Fig. I, the antennas configure ofLTE-A is consulted. The BS employs 4 receive antennas, UEk (k =1,2, ... ,K) employs 2 transmit antennas.

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2010 International Conference on Information, Networking and Automation (ICINA)

VkXk represents the transmitter signal matrix of UEb where Vk represents pre-coding matrix, X k represents

user date matrix. When BS detects the signal of UE1 which can be considered to be desired user, the received UL observation vector y at the BS can be expressed as:

yeO) = H (0)v.(0) X (0) + H (O)V (0) X (0) + I I I 2 2 2 N/ (1) I H(J)V(J) x(J) + N(O) }=I

Where N(O) denotes white noise, Superscript (0) denotes service sector parameters, Superscript G) denotes

interference sector parameters, H2 (0)V2 (0) X2 (0) represents

pairing user's MAl, I;�I HU)VU) XU) represents co­

channel interference of users from other sector.

III. MU-MIMO INTERFERENCE CANCELLATION

A. Educe Matrix Null Space As shown in Fig. 1, for detecting the transmit signal of

user 1 in the BS, the receive observation vector y multiply

transformation matrix T], which can be expressed as:

y'(O) =T.XYCO) =T.xH(0)00)x(0) I I I I I +T.xH (0)v:(0) X (0) + T.xN°) I 2 2 2 I

N/

+1; X Id})0}) XC}) }=I

(2)

Because pairing user and desired user locate in the same sector in MU-MIMO system, MAl accounts for a large proportion of total interference. The goal of MAl cancellation is selecting an appropriate transforming matrix T] in the demodulation, which can

ensure 1; xH2 (O)� (0) X2 (0) = 0 . As X denotes data vector,

T should ensure T. X H (O)V (0) = 0 ] I 2 2 •

Take out channel matrix H2 (0)V2 (0) of user 2, which is the

pairing user of user 1. As users take single stream to transmit, the dimension of channel matrix is 4 xl. Then the

SVD of H2 (0)V2 (0) can be expressed as:

(3)

Where the dimension of U 2 is 4 X 4, column vector of

U2 is the eigenvector of (H/O)V/O») x (H/O)V/O»)H ,

U2s is composed by the subspace of

(H (O)V (0») X (H (O)V (O»)H where the dimension of 2 2 2 2 ' H/O)�(O) is 4xl . So the dimension of U2s is 4xl ,

U2n is composed by the null space of

(H (O)V(O»)x(H (O)V(O»)H dimension is 4x3. Post-2 2 2 2 ' process transformation matrix can be expressed as:

T. = UH and satisfy T. X H (O)V (0) = 0 [11] I 2n ' I 2 2 Substituting post-process transformation matrix into (2), the vector y of the UL received signal can be expressed as:

y'(O) = T. X yeO) = T X H (0)v:(0) X (0) + I 1 1 1 1

N[ (4) T x" H(J)VU) XU) + T X N(O) I L. I }=I

Explicitly, through processing receiving signal which is equivalent to the channel transformation by post-process transformation matrix, MAl can be removed entirely. But the post-process transformation matrix of 3 X 4 can depress the multiplexing gain of spatial channel. That can deteriorate the useful signal intensity.

B. Construct Transformation Matrix Each UE have to transmit data in single stream as in UL

MU-MIMO, adopt 2xl pre-coding matrix. So the post­process transformation matrix TI which obtained by the

pairing user's channel matrix H/0)V2(0) is orthogonal

matrix of 3 X 4 . The operation of processing receiving

signal by post-process transformation matrix TI can be

considered as channel transformation, which can depress the multiplexing gain of spatial channel. That is BS have 3 receive antennas equivalently, which can deteriorate the demodulation of the receiving useful signal and depress the

desired user's signal intensity. Matrix T; of 4x4 can be

composed by constructing one-dimensional vector based

on TI ' match T; X H2 (0)V2 (0) = 0 . On the assumption

that � = [tl' t2, t3 r ' where the dimension of t is 4 xl,

constructing t4 = (tl + t2 + t3)/3 composing

transformation matrix T; = [tl, t2, t3, t4 r Multiplexing gain of spatial channel can be maintained by constructing one-dimension channel information.

C. Restrict User Pairing 3GPP have identified that codebook based pre-coding

was selected in uplink MIMO. In case UE supports two transmitting antennas in L TE-A stage, codebook is formulated as table 1.

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Pre-coding codebook selecting can be based on two ways: Performance and Quantification. The later is selected in this paper. UE generally takes one stream to transfer signal when pairing user is existent.

Codebook selecting and pairing user selecting are both based on user's CSI, but they are unattached. Codebook selecting need apply SVD to channel matrix, and then select the right matrix with the minimum mean square error to the codebook as pre-coding matrix. However, pairing user selecting is processed during resource scheduling in BS. The channel correlation of two users is associated with their relative position, so pairing user select is based on position. But that is not universal.

TABLE!. PRE-CODING CODEBOOK IN UPLINK MIMO WITH TWO TRANSMIT ANTENNAS

Code book index Number of layers

1 2

0 �[:] 1 [1

J20 �] 1 �[�l]

-

2 �[�] -

3 �[_lj] -

4 [l,Ot -

5 [O,lt -

If two users whose channels have a strong correlation take the same codebook and occupancy the same time­spectrum resource, transformation matrix can depress useful signal intensity remarkably. Since pre-coding matrix user selected can characterize CSI of user, pairing user selecting can be restricted. BS share information between codebook selecting and pairing user selecting. User who selects the same codebook can't be paired. That means user who selects the same codebook can't occupancy the same time-spectrum resource, so that the situation that transformation matrix can depress useful signal intensity can be cancelled.

IV. SIMULA nON RESULTS

Performance of the algorithm is simulated based on the parameter and condition defined in ITU-R M.2135[121, simulation parameter as in Table 2.

Cumulative distribution function (CDF) of pairing user's interference, also referred to as MAl in uplink MU­MIMO system, is given in Fig.2. CDF of pairing user's interference which is processed by pairing user interference cancellation algorithm is portrayed in Fig.3. It can be seen

that pairing user's interference can be depressed greatly by applying algorithm.

Fig.4 and Fig.5 portray the CDF of scheduling user's SINR and sector average spectral efficiency (SASE) respectively. Where the dashed line represents the result of uplink MU-MIMO without interference cancellation, the dash-dotted line represents pairing user's MAl cancellation proposed in [9], the solid line represents pairing user's MAl cancellation based on constructing transformation matrix and restricting user pairing proposed in this paper. Though algorithm in [9] can promote scheduling user SINR in Fig.4, pairing user's MAl cancellation algorithm proposed in this paper can promote scheduling user SINR further. So user can have more chance to take high level modulation pattern, and SASE can be promoted at last, as in Fig.5.

TABLE II. SIMULA nON PARAMETER

Parameter Value

Number of Cells 19

Number of Sectors per 3 Cell

Inter-site distance(m) 1732 UE number per sector 10

Antenna Ix2 Configuration

Centre Frequency 800 MHz Traffic model Full Buffer

Shadowing Between 0.5 Correlation cells

Between 1 sectors

Path-Loss 128.1 +37.610g1O(R), R in km

Thermal Noise -174 dBm/Hz Density

BS Antenna A(8)=-min [12(8j83dS,.4", ] pattern(horizontal) (For 3-sector cell (}3dB = 70° , Am = 20 dB

sites)

Figure 2. Pairing user' MAl value without MAl cancellation

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Figure 5. SASE of scheduling user

SASE and Edge spectral efficiency (ESE) are summarized in Table 3. MAl cancellation algorithm by constructing transformation matrix and restricting user pairing proposed in this paper can promote SASE with 10% contrasted with [9].

V. Conclusion

This paper proposes a MAl cancellation algorithm applied in LTE-A uplink MU-MIMO system. This algorithm can cancel MAl of pairing user totally through constructing transformation matrix and restricting user pairing, as well as maintain the multiplexing degree of

spatial channel and minimize the impact of transformation matrix on useful signal intensity. Simulation and analysis show that algorithm in this paper can apply in L TE-A system and promote sector average spectral efficiency contrasted with [9].

TABLE III. COMPARE WITH SPECTRAL EFFICIENCY

SASE ESE (bit/slHz) (bit/slHz)

without MAl 2.0172 0.0774 cancellation

MAl cancellation in 2.2375 0.101 [9]

Proposed MAl 2.4285 0.099 cancellation

ACKNOWLEDGMENT

This work is supported by National Natural Science Foundation of China (60772110), and the Fundamental Research Funds for the Central Universities

[I]

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