TY - JOUR
T1 - A unified analysis of max-min weighted SINR for MIMO downlink system
AU - Cai, Desmond W.H.
AU - Quek, Tony Q.S.
AU - Tan, Chee Wei
N1 - Funding Information:
Manuscript received July 06, 2010; revised December 08, 2010; accepted April 08, 2011. Date of publication May 05, 2011; date of current version July 13, 2011. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Ali Ghrayeb. This work was partially supported by the Research Grants Council of Hong Kong under Project No. RGC CityU 112909, CityU 7200183 and CityU 7008087. The material in this paper has been presented in part at the IEEE International Symposium for Information Theory (ISIT), Austin, Texas, June 2010, and at the Ninth International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Princeton, NJ, May 2011.
PY - 2011/8
Y1 - 2011/8
N2 - This paper studies the max-min weighted signal-to-interference-plus-noise ratio (SINR) problem in the multiple- input-multiple-output (MIMO) downlink, where multiple users are weighted according to priority and are subject to a weighted-sum-power constraint. First, we study the multiple-input-single-output (MISO) and single-input-multiple- output (SIMO) problems using nonlinear Perron-Frobenius theory. As a by-product, we solve the open problem of convergence for a previously proposed MISO algorithm by Wiesel, Eldar, and Shamai in 2006. Furthermore, we unify our analysis with respect to the previous alternate optimization algorithm proposed by Tan, Chiang, and Srikant in 2009, by showing that our MISO result can, in fact, be derived from their algorithm. Next, we combine our MISO and SIMO results into an algorithm for the MIMO problem. We show that our proposed algorithm is optimal when the channels are rank-one, or when the network is operating in the low signal-to-noise ratio (SNR) region. Finally, we prove the parametric continuity of the MIMO problem in the power constraint, and we use this insight to propose a heuristic initialization strategy for improving the performance of our (generally) suboptimal MIMO algorithm. The proposed initialization strategy exhibits improved performance over random initialization.
AB - This paper studies the max-min weighted signal-to-interference-plus-noise ratio (SINR) problem in the multiple- input-multiple-output (MIMO) downlink, where multiple users are weighted according to priority and are subject to a weighted-sum-power constraint. First, we study the multiple-input-single-output (MISO) and single-input-multiple- output (SIMO) problems using nonlinear Perron-Frobenius theory. As a by-product, we solve the open problem of convergence for a previously proposed MISO algorithm by Wiesel, Eldar, and Shamai in 2006. Furthermore, we unify our analysis with respect to the previous alternate optimization algorithm proposed by Tan, Chiang, and Srikant in 2009, by showing that our MISO result can, in fact, be derived from their algorithm. Next, we combine our MISO and SIMO results into an algorithm for the MIMO problem. We show that our proposed algorithm is optimal when the channels are rank-one, or when the network is operating in the low signal-to-noise ratio (SNR) region. Finally, we prove the parametric continuity of the MIMO problem in the power constraint, and we use this insight to propose a heuristic initialization strategy for improving the performance of our (generally) suboptimal MIMO algorithm. The proposed initialization strategy exhibits improved performance over random initialization.
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U2 - 10.1109/TSP.2011.2150218
DO - 10.1109/TSP.2011.2150218
M3 - Article
AN - SCOPUS:79960434421
SN - 1053-587X
VL - 59
SP - 3850
EP - 3862
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 8
M1 - 5762643
ER -