Reconfigurable Intelligent Surface for Next-Generation Networks

  • Jia Ye

Student thesis: Doctoral Thesis

Abstract

Reconfigurable intelligent surfaces (RISs) are now considered among the key enabling technologies catering to the ever-increasing demand for traffic rate in the future fifth-generation beyond or even sixth-generation. RISs can be leveraged to transform the propagation environment into a smart space that can be programmable for the benefit of the communication application. Throughout this proposal, we study RIS-assisted systems from different perspectives to analyze and enhance the operation of such systems in different setups. In this context, we first analyze the performance of the RIS-assisted single-input single-output (SISO) system and make a fair comparison with the conventional relaying system. Then, we investigates the use of a RIS to aid point-to-point multi-data-stream multiple-input multiple-output (MIMO) wireless communications. With practical finite alphabet input, the reflecting elements at the RIS and the precoder at the transmitter are alternatively optimized to minimize the symbol error rate. Considering the same RIS-assisted MIMO system, We further explore the potential of RIS for acting as an active modulator and piggybacking its own information when helping the information transmission between the transmitter and the receiver at the same time. Furthermore, considering a RIS-assisted SISO system over the millimeter wave channel, we propose an appropriate design of the phase shifts of each element at the RIS so as to maximize the received signal power at the desired user, while nulling the received interference signal power at the undesired user. However, most of the works investigated the use of continuous phase shift designs, which cannot be implemented in practice. It motivates us to investigate the control of the phases shifts under the assumption that they belong to a finite discrete set. As the above-mentioned performance analysis and optimization of RIS-assisted system requires the channel state information, we thus address the channel estimation problem for a point-to-point SISO system and a point-to-point multiple-input single-output system, respectively. Finally, we highlight some possible future research directions to be considered for the thesis.
Date of AwardJun 23 2022
Original languageEnglish (US)
Awarding Institution
  • Computer, Electrical and Mathematical Science and Engineering
SupervisorMohamed-Slim Alouini (Supervisor)

Keywords

  • Reconfigurable intelligent surfaces
  • performance Analysis
  • optimization
  • channel estimation

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