Abstract

In this paper, we study wireless power transfer (WPT) using the discrete lens array-based beamspace large-scale multiple-input multiple-output (MIMO) system. The channel matrix of beamspace MIMO exhibits sparse property, which enables the transmitter to employ only a small number of active antennas while maintaining the full MIMO performance. Hence, the number of radio frequency (RF) chains can be significantly reduced, cutting the cost of hardware implementation and circuit power consumption. We consider two WPT design problems in the beamspace MIMO system with constraints on the number of RF chains: the sum power transfer and the max–min power transfer problems; and for each problem, we consider both multi-stream and uni-stream transmissions. For the sum power transfer problem, we show that the uni-stream power transfer achieves the same performance as the multi-stream case, and we propose two algorithms for the uni-stream transmission, namely, an eigendecomposition-based greedy algorithm and a truncated power iteration algorithm. For the max–min power transfer problem, we propose a semidefinite relaxation-based greedy algorithm for the multi-stream power transfer and a Riemannian conjugate gradient algorithm for the uni-stream case. The simulation results show that with a small number of RF chains, the beamspace MIMO system significantly outperforms the conventional MIMO system in terms of WPT efficiency.

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