In this talk, we will discuss low-complexity techniques for the design of intelligent reflecting surfaces (IRS) (also known as reconfigurable intelligent surfaces (RIS)) aided wireless communication systems and their performance. First, we address the optimization of the IRS by random tuning of IRS configurations combined with opportunistic scheduling of users. We show that, with many users in the system, multi-user diversity provides optimal IRS performance without optimizing the IRS. In the second part, we examine how an IRS, being a passive device without bandpass filters, may affect the performance of other mobile network operators when the IRS is deployed and controlled only by a single operator. We address this problem for both sub-6 GHz and mmWave bands, considering centralized and distributed IRS deployment scenarios. Finally, we discuss the issue of wideband beamforming with IRS, where the interplay of spatial wideband effects and phased array architecture of IRSs give rise to the so-called beam-split effects, which severely degrades the array gain and achievable throughput unless treated carefully. We propose two low-complex approaches to handle the beam-split effects: the first is a distributed IRS strategy, which aims at mitigating the beam-split, and the second is an opportunistic OFDMA approach, which positively exploits the beam-split effects. Our theoretical developments and findings are supported by numerical experiments.
Yashvanth received his B.Tech in Electronics and Communication Engineering from NIT Trichy in 2020. He is currently pursuing his PhD under the guidance of Prof. Chandra Murthy at the ECE department in IISc Bangalore, focusing on the design and analysis of intelligent reflecting surfaces for next-generation wireless communication systems. His broad research interests lie in statistical signal processing and applications to wireless communications. He is a recipient of the Prime Minister's Research Fellowship (PMRF).