Title :
Optimality of Beamforming for MIMO Multiple Access Channels Via Virtual Representation
Author :
Wan, Hong ; Chen, Rong-Rong ; Liang, Yingbin
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Utah, Salt Lake City, UT, USA
Abstract :
In this correspondence, we consider the optimality of beamforming for achieving the ergodic capacity of multiple-input multiple-output (MIMO) multiple access channel (MAC) via virtual representation (VR) model. We assume that the receiver knows the channel state information (CSI) perfectly but that the transmitter knows only partial CSI, i.e., the channel statistics. For the single-user case, we prove that the capacity-achieving beamforming angle (c.b.a.) is unique, and there exists a signal-to-noise ratio (SNR) threshold below which beamforming is optimal and above which beamforming is strictly suboptimal. For the multi-user case, we show that the c.b.a is not unique and we obtain explicit conditions that determine the beamforming angles for a special class of correlated MAC-VR models. Under mild conditions, we show that a large class of power allocation schemes can achieve the sum-capacity within a constant as the number of users in the system becomes large. The beamforming scheme, in particular, is shown to be asymptotically capacity-achieving only for certain MAC-VR models.
Keywords :
MIMO communication; array signal processing; correlation methods; multi-access systems; multiuser channels; radio receivers; radio transmitters; wireless channels; CSI; MIMO multiple access channel; MIMO receiver; MIMO transmitter; SNR; capacity-achieving beamforming angle; channel state information; channel statistics; correlated MAC-VR model; multiple-input multiple-output channel; multiuser channel; signal-to-noise ratio; virtual representation; Array signal processing; Channel capacity; Channel state information; MIMO; Permission; Power system modeling; Signal to noise ratio; Statistics; Transmitters; Virtual reality; Beamforming; multiple access; multiple-input multiple-output; power allocation; sum-capacity; virtual representation;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2010.2055241