Downlink MMSE Transceiver Optimization for Multiuser MIMO Systems: MMSE Balancing

• Published in: IEEE transactions on signal processing Vol. 56; no. 8; pp. 3702 - 3712
• Main Authors: Shuying Shi, Schubert, M., Boche, H.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Allocations; Applied sciences; Constraint optimization; Convergence; Derivation; Design engineering; Downlink; Exact sciences and technology; Information, signal and communications theory; Iterative algorithms; Laboratories; Max-min fairness; Mean square error methods; MIMO; Miscellaneous; MMSE; Mobile communication; Optimization; Signal processing; Strategy; Studies; Telecommunications and information theory; transceiver optimization; Transceivers; transceiver optimization; Equity; Downlink; Iterative method; Power allocation; Data broadcast; Information dissemination; Optimization; Transceiver; Mean square error; Multicast; Optimal strategy; Optimal allocation; MMSE; Convergence rate; Max-min fairness; MIMO; Convexity; Uplink; MIMO system; Multiple access; Optimal algorithm; Maximin problem; User requirement; Signal processing; Service quality
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2008.920487

We study the problem of mean square error (MSE) transceiver design for point-to-multipoint transmission in multiuser multiple-input-multiple-output (MIMO) systems. We focus on four optimization problems: minimizing the maximum weighted layer-wise or user-wise MSE under a total power constraint; minimizing the total transmit power subject to a set of layer-wise or user-wise MSE requirements. The non-convexity of these problems makes the derivation of globally optimal algorithms very difficult for transceiver design. New optimal power allocation strategies are derived for the problems considered here. Based on the power allocation, we study how this can be used for iterative transceiver optimization. We propose iterative algorithms and prove the monotonic convergence of the algorithms. The major advantages of the proposed algorithms are their low complexity and fast convergence behavior during the first few iterations. The proposed algorithms are suitable not only for downlink transmission, but also for uplink transmission with a total power constraint.