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Optimal Weighted Antenna Selection For Imperfect Channel Knowledge From Training

Kristem, Vinod and Mehta, Neelesh B and Molisch, Andreas F (2009) Optimal Weighted Antenna Selection For Imperfect Channel Knowledge From Training. In: IEEE International Conference on Communications (ICC 2009), JUN 14-18, 2009, Dresden, pp. 1752-1757.

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Abstract

Receive antenna selection (AS) reduces the hardware complexity of multi-antenna receivers by dynamically connecting an instantaneously best antenna element to the available radio frequency (RF) chain. Due to the hardware constraints, the channels at various antenna elements have to be sounded sequentially to obtain estimates that are required for selecting the ``best'' antenna and for coherently demodulating data. Consequently, the channel state information at different antennas is outdated by different amounts. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, the channel estimates of different antennas should be weighted differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then derive an explicit formula for the optimal selection weights that minimize the SEP. We find that when selection weights are not used, the SEP need not improve as the number of antenna elements increases, which is in contrast to the ideal channel estimation case. However, the optimal selection weights remedy this situation and significantly improve performance.

Item Type: Conference Paper
Additional Information: Copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 08 Sep 2010 08:25
Last Modified: 19 Sep 2010 06:15
URI: http://eprints.iisc.ernet.in/id/eprint/32037

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