IRS-Aided Overloaded Multi-Antenna Systems: Joint User Grouping and Resource Allocation
Ying Gao, Qingqing Wu, Wen Chen, Yang Liu, Ming Li, Daniel Benevides, da Costa

TL;DR
This paper develops user grouping and resource allocation strategies for IRS-assisted overloaded multi-antenna SWIPT systems, improving throughput and energy harvesting performance despite phase errors.
Contribution
It introduces two novel user grouping schemes and efficient algorithms for joint optimization in overloaded IRS-aided SWIPT systems with phase errors.
Findings
User grouping significantly enhances throughput.
Robust designs outperform non-robust counterparts under phase errors.
Overlapping user grouping is more effective when K is close to M.
Abstract
This paper studies an intelligent reflecting surface (IRS)-aided multi-antenna simultaneous wireless information and power transfer (SWIPT) system where an -antenna access point (AP) serves single-antenna information users (IUs) and single-antenna energy users (EUs) with the aid of an IRS with phase errors. We explicitly concentrate on overloaded scenarios where and . Our goal is to maximize the minimum throughput among all the IUs by optimizing the allocation of resources (including time, transmit beamforming at the AP, and reflect beamforming at the IRS), while guaranteeing the minimum amount of harvested energy at each EU. Towards this goal, we propose two user grouping (UG) schemes, namely, the non-overlapping UG scheme and the overlapping UG scheme, where the difference lies in whether identical IUs can exist in multiple groups. Different IU groups…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Antenna Design and Analysis · Underwater Vehicles and Communication Systems
