Capacity limits of MIMO channels

被引:1502
作者
Goldsmith, A [1 ]
Jafar, SA [1 ]
Jindal, N [1 ]
Vishwanath, S [1 ]
机构
[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
关键词
antenna correlation; beamforming; broadcast channels (BCs); channel distribution information (CDI); channel state information (CSI); multicell systems; multiple-access channels (MACs); multiple-input multiple-output (MIMO) channels; multiuser systems; Shannon capacity;
D O I
10.1109/JSAC.2003.810294
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We provide an overview of the extensive recent results on the Shannon capacity of single-user and multiuser multiple-input multiple-output (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about the underlying time-varying channel model and how well it can be tracked at the receiver, as well as at the transmitter. More realistic assumptions can dramatically impact the potential capacity gains of MIMO techniques. For time-varying MIMO channels there are multiple Shannon theoretic capacity definitions and, for each definition, different correlation models and channel information assumptions that we consider. We first provide a comprehensive summary of ergodic and capacity versus outage results for single-user MIMO channels. These results indicate that the capacity gain obtained from multiple antennas heavily depends on the available channel information at either the receiver or transmitter, the channel signal-to-noise ratio, and the correlation between the channel gains on each antenna element. We then focus attention on the capacity region of the multiple-access channels (MACs) and the largest known achievable rate region for the broadcast channel. In contrast to single-user MIMO channels, capacity results for these multiuser MIMO channels are quite difficult to obtain, even for constant channels. We. summarize results for the MIMO broadcast and MAC for channels that are either constant or fading with perfect instantaneous knowledge of the antenna gains at,both transmitter(s) and receiver(s). We show that the capacity region of the MIMO multiple access and the largest known achievable rate region (called the dirty-paper region) for the MIMO broadcast channel are intimately related via a duality transformation. This transformation facilitates finding the transmission strategies that achieve a point on the boundary of the MIMO MAC capacity region in terms of the transmission strategies of the MIMO broadcast dirty-paper region and vice-versa. Finally, we discuss capacity results for multicell MIMO channels with base station cooperation. The base stations then act as a spatially diverse antenna array and transmission strategies that exploit this structure exhibit significant capacity gains. This section also provides a brief discussion of system level issues associated with MIMO cellular. Open problems in this field abound and are discussed throughout the paper.
引用
收藏
页码:684 / 702
页数:19
相关论文
共 87 条
[1]   A space-time correlation model for multielement antenna systems in mobile fading channels [J].
Abdi, A ;
Kaveh, M .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2002, 20 (03) :550-560
[2]   Space-time processing for broadband wireless access [J].
Al-Dhahir, N ;
Fragouli, C ;
Stamoulis, A ;
Younis, W ;
Calderbank, R .
IEEE COMMUNICATIONS MAGAZINE, 2002, 40 (09) :136-142
[3]   Overview and comparison of equalization schemes for space-time-coded signals with application to EDGE [J].
Al-Dhahir, N .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2002, 50 (10) :2477-2488
[4]   Fading channels: Information-theoretic and communications aspects [J].
Biglieri, E ;
Proakis, J ;
Shamai, S .
IEEE TRANSACTIONS ON INFORMATION THEORY, 1998, 44 (06) :2619-2692
[5]  
Bölcskei H, 2002, IEEE T COMMUN, V50, P225, DOI 10.1109/26.983319
[6]  
Borst S., 2001, USE DIVERSITY ANTENN
[7]  
Boyd S., 2001, INTRO CONVEX OPTIMIZ
[8]   On the capacity of some channels with channel state information [J].
Caire, G ;
Shamai, S .
IEEE TRANSACTIONS ON INFORMATION THEORY, 1999, 45 (06) :2007-2019
[9]  
Caire G., 2000, P 38 ANN ALL C COMM, P1188
[10]   Adaptive modulation and MIMO coding for broadband wireless data networks [J].
Catreux, S ;
Erceg, V ;
Gesbert, D ;
Heath, RW .
IEEE COMMUNICATIONS MAGAZINE, 2002, 40 (06) :108-115