TY - GEN
T1 - Decomposing the MIMO broadcast channel
AU - Khina, Anatoly
AU - Kochman, Yuval
AU - Erez, Uri
PY - 2010
Y1 - 2010
N2 - The problem of transmitting a common message over a multiple-input multiple-output (MIMO) Gaussian broadcast channel with multiple receivers is well understood in terms of capacity. Nevertheless, existing optimal (capacity-achieving) schemes for this scenario require joint decoding of the multiple streams transmitted, entailing high computational complexity. In this paper, a low-complexity scheme requiring only single stream decoding is proposed. The scheme uses a matrix decomposition, which allows, by linear pre- and post-processing, to simultaneously transform both channel matrices to triangular forms, where the diagonal entries of both channels are equal. In conjunction with successive interference cancellation at each receiver, parallel channels are created, over each of which scalar coding and decoding may be used. We prove that this channel transformation conserves mutual information, and hence any sub-optimality of the proposed scheme is governed solely by the gap-to-capacity of the scalar coding scheme over the parallel channels.
AB - The problem of transmitting a common message over a multiple-input multiple-output (MIMO) Gaussian broadcast channel with multiple receivers is well understood in terms of capacity. Nevertheless, existing optimal (capacity-achieving) schemes for this scenario require joint decoding of the multiple streams transmitted, entailing high computational complexity. In this paper, a low-complexity scheme requiring only single stream decoding is proposed. The scheme uses a matrix decomposition, which allows, by linear pre- and post-processing, to simultaneously transform both channel matrices to triangular forms, where the diagonal entries of both channels are equal. In conjunction with successive interference cancellation at each receiver, parallel channels are created, over each of which scalar coding and decoding may be used. We prove that this channel transformation conserves mutual information, and hence any sub-optimality of the proposed scheme is governed solely by the gap-to-capacity of the scalar coding scheme over the parallel channels.
KW - Broadcast channel
KW - GDFE
KW - Geometric mean decomposition
KW - MIMO channel
KW - MMSE
KW - Successive decoding
KW - Successive interference cancellation
KW - Zero-forcing
UR - http://www.scopus.com/inward/record.url?scp=79952399932&partnerID=8YFLogxK
U2 - 10.1109/ALLERTON.2010.5706894
DO - 10.1109/ALLERTON.2010.5706894
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AN - SCOPUS:79952399932
SN - 9781424482146
T3 - 2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
SP - 102
EP - 106
BT - 2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
T2 - 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
Y2 - 29 September 2010 through 1 October 2010
ER -