SDR-Based Precoding for Multi-User Multi-Stream MIMO Downlinks

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The existing methods based on convex-optimization theory, which use the concept of SINR, can just design the optimal precoder for each user with single antenna. In this paper, we design the optimal precoding matrices for multi-user MIMO downlinks by solving the optimization problem that minimizes total transmit power subject to signal-leakage-plus-noise-ratio (SLNR) constraints. Because SLNR of each user is determined by its own precoding matrix and is independent of other users, the goal problem can be separated into a series of decoupled low-complexity quadratically constrained quadratic programs (QCQPs). Using the semidefinite relaxation (SDR) technique, these QCQPs can be reformulated into the semidefinite programs (SDP) and be solved effectively. Simulation results show that proposed precoding scheme is quite feasible when each user has two receive antennas, and it has better bit error rate (BER) performance than the original maximal-SLNR precoding scheme when SLNR of each user satisfies large threshold value.

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March 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] A. Wiesel, Y. C. Eldar and S. Shamai. Linear precoding via conic semidefinite optimization for fixed MIMO receivers. IEEE Trans. Signal Processing , vol. 54, no. 3, pp.161-176, (2006).

DOI: 10.1109/tsp.2005.861073

Google Scholar

[2] Z. Q. Luo and W. Yu. An introduction to convex optimization for communications and signal processing. IEEE Selected Areas in Communications, vol. 24, no. 8, pp.1426-1438, (2006).

DOI: 10.1109/jsac.2006.879347

Google Scholar

[3] Luo Z Q, Ma W K, and So A M, Semidefinite relaxation of quadratic optimization problems, IEEE signal processing magazine, special issue on convex optimization for signal processing, pp.20-34, May (2010).

DOI: 10.1109/msp.2010.936019

Google Scholar

[4] M. B. Shenouda and T. N. Davidson. Linear matrix inequality formulations of robust QoS precoding for broadcast channels. CCECE'2007. Vancouver, BC, Canada: IEEE Press, 2007: 324-328.

DOI: 10.1109/ccece.2007.87

Google Scholar

[5] M. Sadek, A. Tarighat and A. H. Sayed. A leakage-based precoding scheme for downlink multi-user MIMO channels. IEEE Trans. Wireless Comm., vol. 6, no. 5, pp.1711-1721, (2007).

DOI: 10.1109/twc.2007.360373

Google Scholar

[6] M. Grant and S Boyd. Cvx users' Guide for cvx version 1. 21. online. http: /c1319062. cdn. cloudfiles. rackspacecloud. com/cvx_usrguide. pdf, 2010, 7.

Google Scholar