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Training-Based Antenna Selection for PER Minimization: A POMDP Approach

Padmanabhan, Sinchu and Stephen, Reuben George and Murthy, Chandra R and Coupechoux, Marceau (2015) Training-Based Antenna Selection for PER Minimization: A POMDP Approach. In: IEEE TRANSACTIONS ON COMMUNICATIONS, 63 (9). pp. 3247-3260.

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Official URL: http://dx.doi.org/http://dx.doi.org/10.1109/TCOMM....

Abstract

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Keywords: Antenna selection; POMDP; myopic policy; finite state Markov chain
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Division of Electrical Sciences > Electrical Engineering
Depositing User: Id for Latest eprints
Date Deposited: 15 Oct 2015 06:35
Last Modified: 15 Oct 2015 06:35
URI: http://eprints.iisc.ac.in/id/eprint/52557

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