An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems

By Cunhua Pan, Gui Zhou, Kangda Zhi, Sheng Hong, Tuo Wu, Yi-Han Pan, Hong Ren, M. Di Renzo, A. L. Swindlehurst, Rui Zhang and 1 more. IEEE Journal on Selected Topics in Signal Processing, 2021

772 citations recorded by the source corpus.

In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes. However, the improvements through applying such schemes operating only at two endpoints (i.e., transmitter and receiver) are limited even after five generations of wireless systems. Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) have emerged as a new and promising technology that can configure the wireless environment in a favorable manner by properly tuning the phase shifts of a large number of quasi passive and low-cost reflecting elements, thus standing out as a promising candidate technology for the next/sixth-generation (6G) wireless system. However, to reap the performance benefits promised by RIS/IRS, efficient signal processing techniques are crucial, for a variety of purposes such as channel estimation, transmission design, radio localization, and so on. In this paper, we provide a comprehensive overview of recent advances on RIS/IRS-aided wireless systems from the signal processing perspective.We also highlight promising research directions that are worthy of investigation in the future.

Subfields: Electrical and Electronic Engineering, Genetics, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/59eaadd5e977d60083207c1d22bd969d35e82d58

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Citations in the corpus

Joint Transmit Waveform and Passive Beamforming Design for RIS-Aided DFRC Systems (2021, background): “Attracted by above advantages, RIS is deemed a crucial enabling technology for achieving intelligent radio environment in 6G networks and has received significant attentions from both industry and academia [9].”