Massive Wireless Energy Transfer With Statistical CSI Beamforming

Wireless energy transfer (WET) is a promising solution to enable massive machine-type communications (mMTC) with low-complexity and low-powered wireless devices. Given the restrictions of devices, instant channel state information at transmitter (CSIT) not expected be available in practical WET-enabled mMTC. However, because it common that terminals appear spatially clustered, some degree spatial correlation between their channels base station (BS) occur. The paper considers antenna array BS for WET only has access i) first second order statistics Rician component multiple-input multiple-output (MIMO) also ii) line-of-sight MIMO component. optimal precoding scheme maximizes total single-antenna devices derived considering continuous alphabet precoders, permitting any modulated or deterministic waveform. This may lead clusters being assigned low fraction power cluster, creating rather uneven situation among them. Consequently, fairness criterion introduced, imposing minimum amount allocated terminals. A piece-wise linear harvesting circuit considered terminals, both saturation sensitivity, constrained version precoder proposed by solving non-linear programming problem. paramount benefit encompassment allocation different clusters. Moreover, given polynomial complexity increase unconstrained precoder, observed gain system's sum-power an increasing number antennas ULA, use arrays desirable.