Phase-Shift and Transmit Power Optimization for RIS-Aided Massive MIMO SWIPT IoT Networks
Mohammadali Mohammadi, Hien Quoc Ngo, Michail Matthaiou

TL;DR
This paper proposes a RIS-assisted massive MIMO framework for SWIPT IoT networks, optimizing transmit power and phase shifts to enhance energy harvesting and spectral efficiency amidst channel uncertainties.
Contribution
It introduces a two-timescale transmission scheme with joint optimization of BS power and RIS phase shifts, accounting for channel estimation errors and pilot contamination.
Findings
Average harvested energy improved by 132% with the proposed algorithm.
Pilot contamination can double the energy harvesting potential in some scenarios.
Closed-form spectral efficiency expressions derived under practical channel conditions.
Abstract
We investigate reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) Internet of Things (IoT) networks, where energy-limited IoT devices are overlaid with cellular information users (IUs). IoT devices are wirelessly powered by a RIS-assisted massive multiple-input multiple-output (MIMO) base station (BS), which is simultaneously serving a group of IUs. By leveraging a two-timescale transmission scheme, precoding at the BS is developed based on the instantaneous channel state information (CSI), while the passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. We derive closed-form expressions for the achievable spectral efficiency of the IUs and average harvested energy at the IoT devices, taking the channel estimation errors and pilot contamination into account. Then, a non-convex max-min fairness…
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Taxonomy
TopicsWireless Body Area Networks · Energy Harvesting in Wireless Networks · Advanced Wireless Communication Technologies
