Joint Beamforming and Phase Shift Optimization for Multicell IRS-aided OFDMA-URLLC Systems
Walid R. Ghanem, Vahid Jamali, and Robert Schober

TL;DR
This paper introduces a novel joint beamforming and phase shift optimization algorithm for IRS-assisted multicell OFDMA-URLLC systems, significantly improving reliability and throughput in low-latency communication networks.
Contribution
It is the first to study IRS-enhanced OFDMA-URLLC systems and proposes a practical iterative algorithm for resource allocation with guaranteed convergence.
Findings
Achieves substantial throughput gains over baseline schemes.
Enhances URLLC reliability through IRS deployment.
Provides a convergent suboptimal optimization algorithm.
Abstract
This paper investigates the resource allocation algorithm design for intelligent reflecting surface (IRS) aided multiple-input single-output (MISO) orthogonal frequency division multiple access (OFDMA) multicell networks, where a set of base stations cooperate to serve a set of ultra-reliable low-latency communication (URLLC) users. The IRS is deployed to enhance the communication channel and increase reliability by creating a virtual line of sight for URLLC users with unfavorable propagation conditions. This is the first study on IRS-enhanced OFDMA-URLLC systems. The resource allocation algorithm design is formulated as an optimization problem for the maximization of the weighted system sum throughput while guaranteeing the quality of service of the URLLC users. The optimization problem is non-convex and finding the globally optimal solution entails a high computational complexity…
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