Mixed-Timescale Beamforming and Power Splitting for Massive MIMO Aided SWIPT IoT Network
Traditional simultaneous wireless information and power transfer (SWIPT) with power splitting assumes perfect channel state information (CSI), which is difficult to obtain especially in the massive multiple-input-multiple-output (MIMO) regime. In this letter, we consider a mixed-timescale joint beamforming and power splitting (MJBP) scheme to maximize general utility functions under a power constraint in the downlink of a massive MIMO SWIPT IoT network. In this scheme, the transmit digital beamformer is adapted to the imperfect CSI, while the receive power splitters are adapted to the long-term channel statistics only due to the consideration of hardware limit and signaling overhead. The formulated optimization problem is solved using a mixed-timescale online stochastic successive convex approximation (MO-SSCA) algorithm. Simulation results reveal significant gain over the baselines.
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