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Asymptotic analysis of max-min weighted SINR in multiuser downlink

Huang, Yichao and Tan, Chee Wei and Rao, Bhaskar D. (2012) Asymptotic analysis of max-min weighted SINR in multiuser downlink. In: 46th Annual Conference on Information Sciences and Systems (CISS). IEEE , Piscataway, NJ, pp. 1-5. ISBN 978-1-4673-3139-5.

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In this paper, we study the problem of jointly optimizing the beamformer and the power in a multiuser downlink system wherein the number of transmit antennas and the number of users grow asymptotically large with a bounded ratio. The max-min weighted SINR problem with a weighted sum power constraint is considered. Techniques developed from random matrix theory are employed to derive asymptotically optimal solutions that only rely on statistical channel information and can be further leveraged to design the asymptotically optimal beamformers in a non-iterative manner. Moreover, by using nonlinear Perron-Frobenius theory and random matrix theory, an effective uplink system and an effective downlink system are proposed to characterize and interpret the asymptotically optimal solutions.

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Additional Information:© 2012 IEEE. The work of Y. Huang and B. D. Rao was supported by Ericsson endowed chair funds, the Center for Wireless Communications, UC Discovery grant com09R-156561 and NSF grant CCF-1115645. The work of C. W. Tan was supported by grants from the Research Grants Council of Hong Kong, Project No. RGC CityU 112909, and Qualcomm Inc.
Funding AgencyGrant Number
University of Californiacom09R-156561
Research Grants Council of Hong KongRGC CityU 112909
Subject Keywords:Power control, beamforming, nonlinear Perron-Frobenius theory, asymptotic analysis, effective downlink, effective uplink
Record Number:CaltechAUTHORS:20170810-130031875
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Official Citation:Y. Huang, Chee Wei Tan and B. D. Rao, "Asymptotic analysis of max-min weighted SINR in multiuser downlink," 2012 46th Annual Conference on Information Sciences and Systems (CISS), Princeton, NJ, 2012, pp. 1-5. doi: 10.1109/CISS.2012.6310750 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:80173
Deposited By: Zhaojian Wang
Deposited On:11 Aug 2017 22:31
Last Modified:15 Nov 2021 17:53

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