Power Optimization in Multi-IRS Aided Delay-Constrained IoVT Systems

TL;DR

This paper introduces a multi-IRS aided IoVT system that optimizes power and beamforming to reduce power consumption under delay constraints, demonstrating significant improvements over benchmarks through simulation.

Contribution

It proposes a joint power control and passive beamforming optimization framework for multi-IRS IoVT systems under delay constraints, using Lyapunov and fractional programming techniques.

Findings

Significant power savings compared to benchmark algorithms.

Effective trade-off between IRS elements and system performance.

Validated through extensive simulations.

Abstract

With the advancement of video sensors in the Internet of Things, Internet of Video Things (IoVT) systems, capable of delivering abundant and diverse information, have been increasingly deployed for various applications. However, the extensive transmission of video data in IoVT poses challenges in terms of delay and power consumption. Intelligent reconfigurable surface (IRS), as an emerging technology, can enhance communication quality and consequently improve system performance by reconfiguring wireless propagation environments. Inspired by this, we propose a multi-IRS aided IoVT system that leverages IRS to enhance communication quality, thereby reducing power consumption while satisfying delay requirements. To fully leverage the benefits of IRS, we jointly optimize power control for IoVT devices and passive beamforming for IRS to minimize long-term total power consumption under delay constraints. To solve this problem, we first utilize Lyapunov optimization to decouple the long-term optimization problem into each time slot. Subsequently, an alternating optimization algorithm employing optimal solution-seeking and fractional programming is proposed to effectively solve the optimization problems at each time slot. Simulation results demonstrate that the proposed algorithm significantly outperforms benchmark algorithms in terms of long-term total power consumption. Moreover, a trade-off between the number of IRS elements and system performance is also proved.