A Novel Energy-Efficient Training Method for Receive Antenna Selection

Receive antenna selection (AS), in which only a subset of antennas receive simultaneously at any time, requires the transmitter to send pilots multiple times so that the receiver can acquire channel state of all antennas and select the best subset. In conventional AS training, sensitivity of coherent reception to channel estimation errors forces the transmitter to boost the energy allocated to all pilots to ensure accurate channel estimates. Energy for pilots received by unselected antennas is mostly wasted, especially since the selection process is robust to estimation errors. In this paper, we propose a novel training method uniquely tailored for AS. Using one extra pilot symbol, accurate channel estimates get generated for the antenna subset that actually receives data. Consequently, the transmitter can selectively boost the energy allocated to the extra pilot. Other pilots, which now primarily help in subset selection, get allocated less energy. We derive closed-form expressions for the proposed scheme's symbol error probability, and optimize the energy allocated to pilot and data symbols. We show that the optimal solution achieves full diversity; it is provably unique and strictly better than the conventional model.