Pilot Allocation and Receive Antenna Selection: A Markov Decision Theoretic Approach

Abstract :

This paper considers antenna selection (AS) for packet reception at a receiver equipped with multiple antenna elements but only a single radio frequency chain. The receiver makes its AS decisions based on noisy channel estimates obtained from the training symbols (pilots). The time-correlation of the wireless channel and the results of the link-layer error checks upon data packet reception provide additional information that can be exploited for AS. This information can also be used to optimally distribute pilots among the antenna elements, so that packet loss due to selection errors is minimized. The task of the receiver, then, is to sequentially select (a) the pilot symbol allocation for channel estimation on each of the receive antennas and (b) the antenna to be used for data packet reception. The goal is to maximize the expected throughput, based on the history of allocation and selection decisions, and the corresponding noisy channel estimates and error check observations. This joint problem of pilot allocation and AS is solved as a partially observed Markov decision problem (POMDP) and the solutions yield the optimal policies that maximize the long-term expected throughput. The performance of the POMDP solution is compared with several other schemes for a 2-state Markov channel model, and it is illustrated that it outperforms the others.

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Reuben G. Stephen, Chandra R. Murthy, Marceau Coupechoux. Pilot Allocation and Receive Antenna Selection: A Markov Decision Theoretic Approach. IEEE International Conference on Communications (ICC), Jun 2013, Budapest, Hungary. pp.1-6. ⟨hal-01144313⟩

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