A Novel Energy-Efficient Optimization Technique for Intelligent Transportation Systems

Abstract

In this chapter, we investigate the energy efficiency (EE) of the intelligent reflecting surface (IRS)–assisted intelligent transportation system (ITS) under both the Rayleigh and Nakagami-m fading conditions. Since its inception, ITS is growing rapidly, as it helps to provide seamless data transfer between vehicles, avail safe transportation, and avoid accidents. Nevertheless, the amount of data processed in ITS demands more transmission power. To address this, IRS blocks with several passive reflective elements have been recognized as a promising technology to reduce power consumption and enhance EE. In recent years, with the rapid increase in data usage, mobile users demand more transmission power. It is difficult to satisfy all users with limited transmission power; however, IRS has the ability to solve the power requirement problem by using the reflecting elements. In our chapter, two different fading environments (i.e., Rayleigh, Nakagami-m) are adopted to meet the needs for the practical implementations of IRS-assisted ITS. In addition to this, the phase-shift optimization of each IRS element becomes a challenging task which also makes it difficult to estimate the channel for IRS-assisted ITS. To overcome the above challenges and optimize the EE, we develop a novel IRS element clustering method and a passive beamforming technique based on the desired location of the ITS. Furthermore, we analyze the EE and also spectral efficiency of the IRS-assisted ITS with multiple IRS blocks. Numerical results show that the multiple IRS blocks can significantly improve the ITS performance in terms of EE © 2024 selection and editorial matter, Dr. Abraham George and G. Ramana Murthy; individual chapters, the contributors.