Mixed-Timescale Beamforming and Power Splitting for Massive MIMO Aided SWIPT IoT Network

TL;DR

This paper proposes a mixed-timescale joint beamforming and power splitting scheme for massive MIMO SWIPT IoT networks, optimizing performance under imperfect CSI and hardware constraints using an online stochastic algorithm.

Contribution

It introduces a novel mixed-timescale optimization framework that adapts beamforming to imperfect CSI and power splitting to long-term channel statistics.

Findings

Significant performance gains over baseline schemes.

Effective handling of imperfect CSI in massive MIMO SWIPT.

Demonstrated robustness to hardware limitations.

Abstract

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.