Title :
WLC36-5: Rank-Reduction of Large MIMO Channels
Author :
Bagley, Zachary ; Schlegel, Christian
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Utah, Salt Lake City, UT
fDate :
Nov. 27 2006-Dec. 1 2006
Abstract :
Multiple-input-multiple-output (MIMO) systems are capable of delivering substantially higher throughput under favorable circumstances, at the cost of complexity in terms of the number of parameters that must be estimated and processed. Our results are directed toward lowering this computational complexity through reduction of channel information required at the transmitter. Specifically, we examine the case when only the number of degrees of freedom supporting a threshold SNR is known at the transmitter. We show capacity is maximized in this case with a rank-reduced MIMO channel and an equal power distribution over all available antennas. The number of independent sequences to transmit, i.e. the amount of rank-reduction, is computed by defining the problem such that the optimal number of active data sequences is a capacity maximization problem solvable at the receiver whose results are used at the transmitter. It is shown that in the absence of channel state information, the received SNR for each potential sub-channel is sufficient to determine the optimal number of independent data sequences to transmit.
Keywords :
MIMO communication; MIMO systems; channel capacity; channel estimation; optimisation; wireless channels; capacity maximization problem; channel information reduction; computational complexity; data sequences; large MIMO channels; multiple-input-multiple-output systems; rank reduction; Channel state information; Cities and towns; Computational complexity; Computer vision; Costs; Gaussian noise; MIMO; Power distribution; Throughput; Transmitters;
Conference_Titel :
Global Telecommunications Conference, 2006. GLOBECOM '06. IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
1-4244-0356-1
Electronic_ISBN :
1930-529X
DOI :
10.1109/GLOCOM.2006.827