Downlink Clustering-Based Scheduling of IRS-Assisted Communications With Reconfiguration Constraints

Fuente: arXiv
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Autori principali: Rech, Alberto, Pagin, Matteo, Badia, Leonardo, Tomasin, Stefano, Giordani, Marco, Gambini, Jonathan, Zorzi, Michele
Natura: Preprint
Pubblicazione: 2023
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author Rech, Alberto
Pagin, Matteo
Badia, Leonardo
Tomasin, Stefano
Giordani, Marco
Gambini, Jonathan
Zorzi, Michele
author_facet Rech, Alberto
Pagin, Matteo
Badia, Leonardo
Tomasin, Stefano
Giordani, Marco
Gambini, Jonathan
Zorzi, Michele
contents Intelligent reflecting surfaces (IRSs) are being widely investigated as a potential low-cost and energy-efficient alternative to active relays for improving coverage in next-generation cellular networks. However, technical constraints in the configuration of IRSs should be taken into account in the design of scheduling solutions and the assessment of their performance. To this end, we examine an IRS-assisted time division multiple access (TDMA) cellular network where the reconfiguration of the IRS incurs a communication cost; thus, we aim at limiting the number of reconfigurations over time. Along these lines, we propose a clustering-based heuristic scheduling scheme that maximizes the cell sum capacity, subject to a fixed number of reconfigurations within a TDMA frame. First, the best configuration of each user equipment (UE), in terms of joint beamforming and optimal IRS configuration, is determined using an iterative algorithm. Then, we propose different clustering techniques to divide the UEs into subsets sharing the same sub-optimal IRS configuration, derived through distance- and capacity-based algorithms. Finally, UEs within the same cluster are scheduled accordingly. We provide extensive numerical results for different propagation scenarios, IRS sizes, and phase shifters quantization constraints, showing the effectiveness of our approach in supporting multi-user IRS systems with practical constraints.
format Preprint
id arxiv_https___arxiv_org_abs_2305_14051
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Downlink Clustering-Based Scheduling of IRS-Assisted Communications With Reconfiguration Constraints
Rech, Alberto
Pagin, Matteo
Badia, Leonardo
Tomasin, Stefano
Giordani, Marco
Gambini, Jonathan
Zorzi, Michele
Signal Processing
Networking and Internet Architecture
Intelligent reflecting surfaces (IRSs) are being widely investigated as a potential low-cost and energy-efficient alternative to active relays for improving coverage in next-generation cellular networks. However, technical constraints in the configuration of IRSs should be taken into account in the design of scheduling solutions and the assessment of their performance. To this end, we examine an IRS-assisted time division multiple access (TDMA) cellular network where the reconfiguration of the IRS incurs a communication cost; thus, we aim at limiting the number of reconfigurations over time. Along these lines, we propose a clustering-based heuristic scheduling scheme that maximizes the cell sum capacity, subject to a fixed number of reconfigurations within a TDMA frame. First, the best configuration of each user equipment (UE), in terms of joint beamforming and optimal IRS configuration, is determined using an iterative algorithm. Then, we propose different clustering techniques to divide the UEs into subsets sharing the same sub-optimal IRS configuration, derived through distance- and capacity-based algorithms. Finally, UEs within the same cluster are scheduled accordingly. We provide extensive numerical results for different propagation scenarios, IRS sizes, and phase shifters quantization constraints, showing the effectiveness of our approach in supporting multi-user IRS systems with practical constraints.
title Downlink Clustering-Based Scheduling of IRS-Assisted Communications With Reconfiguration Constraints
topic Signal Processing
Networking and Internet Architecture
url https://arxiv.org/abs/2305.14051