Journal ArticleDOI
Capacity limits of MIMO channels
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An overview of the extensive results on the Shannon capacity of single-user and multiuser multiple-input multiple-output (MIMO) channels is provided and it is shown that the capacity region of the MIMO multiple access and the largest known achievable rate region (called the dirty-paper region) for the M IMO broadcast channel are intimately related via a duality transformation.Abstract:
We provide an overview of the extensive 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.read more
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References
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TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI
Capacity of Multi‐antenna Gaussian Channels
TL;DR: In this paper, the authors investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading, and derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas.
Journal ArticleDOI
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
G. J. Foschini,M. J. Gans +1 more
TL;DR: In this article, the authors examined the performance of using multi-element array (MEA) technology to improve the bit-rate of digital wireless communications and showed that with high probability extraordinary capacity is available.
Journal ArticleDOI
Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas
TL;DR: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver with the aim of leveraging the already highly developed 1-D codec technology.
Journal ArticleDOI
Writing on dirty paper (Corresp.)
TL;DR: It is shown that the optimal transmitter adapts its signal to the state S rather than attempting to cancel it, which is also the capacity of a standard Gaussian channel with signal-to-noise power ratio P/N.
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