Phase-Shift and Transmit Power Optimization for RIS-Aided Massive MIMO SWIPT IoT Networks

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Main Authors: Mohammadi, Mohammadali, Ngo, Hien Quoc, Matthaiou, Michail
Format: Preprint
Published: 2024
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author Mohammadi, Mohammadali
Ngo, Hien Quoc
Matthaiou, Michail
author_facet Mohammadi, Mohammadali
Ngo, Hien Quoc
Matthaiou, Michail
contents 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 optimization problem is formulated subject to the power budget at the BS and individual quality of service requirements of IUs, where the transmit power levels at the BS and passive RIS reflection coefficients are jointly optimized. Our simulation results show that the average harvested energy at the IoT devices can be improved by $132\%$ with the proposed resource allocation algorithm. Interestingly, IoT devices benefit from the pilot contamination, leading to a potential doubling of the harvested energy in certain network configurations.
format Preprint
id arxiv_https___arxiv_org_abs_2407_12478
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Phase-Shift and Transmit Power Optimization for RIS-Aided Massive MIMO SWIPT IoT Networks
Mohammadi, Mohammadali
Ngo, Hien Quoc
Matthaiou, Michail
Information Theory
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 optimization problem is formulated subject to the power budget at the BS and individual quality of service requirements of IUs, where the transmit power levels at the BS and passive RIS reflection coefficients are jointly optimized. Our simulation results show that the average harvested energy at the IoT devices can be improved by $132\%$ with the proposed resource allocation algorithm. Interestingly, IoT devices benefit from the pilot contamination, leading to a potential doubling of the harvested energy in certain network configurations.
title Phase-Shift and Transmit Power Optimization for RIS-Aided Massive MIMO SWIPT IoT Networks
topic Information Theory
url https://arxiv.org/abs/2407.12478