Matrix-lifting semi-definite programming for detection in multiple antenna systems

Authors:
Amin Mobasher;Renata Sotirov;Amir K. Khandani
Affiliations:
Research In Motion Limited,Waterloo, ON, Canada;Department of Econometrics and Operations Research, Tilburg University, Tilburg, The Netherlands;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
Venue:
IEEE Transactions on Signal Processing
Year:
2010

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Abstract

This paper presents a computationally efficient decoder for multiple antenna systems. The proposed algorithm can be used for any constellation (QAM or PSK) and any labeling method. The decoder is based on matrix-lifting semidefinite programming (SDP). The strength of the proposed method lies in a new relaxation approach applied to the previous work by Mobasher et al. This results in a reduction of the number of variables from (NK + 1)(NK + 2)/2, in the previous work by Mobasher et al. to (2N + K)2, in the new method, where is twice the number of transmit antennas and K is the number of constellation points in each real dimension. It is shown that this reduction in the number of variables results in a significant computational complexity reduction compared to the previous work by Mobasher et al. Moreover, the proposed method offers a better symbol error rate performance as compared to some known and recent SDP-based quasi-maximum likelihood detection methods reported in the literature.