Sum-Rate Maximization for RIS-Assisted Integrated Sensing and Communication Systems With Manifold Optimization

Eyad Shtaiwi, Hongliang Zhang, Ahmed Abdelhadi, A. Lee Swindlehurst, Zhu Han, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Integrated sensing and communication (ISAC) is a key enabler for next-generation wireless communication systems to improve spectral efficiency. However, the coexistence of sensing and communication functionalities can cause harmful interference. In this paper, we propose to use a reconfigurable intelligent surface (RIS) in conjunction with ISAC to address this issue. The RIS is composed of a large number of low-cost elements that can adjust the amplitude and phase shift of impinging signals, thus providing a relatively high beamforming gain. To maximize the sum-rate of the communication system, we jointly optimize the beamformer at the base station (BS) and the phase shifts at the RIS, subject to a threshold on the interference power, the unit-norm constraint of the transmit power, and the unit modulus constraint of the RIS phase shifts. To efficiently tackle this NP-hard problem, we first reformulate the problem into a more tractable form using the fractional programming (FP) technique. Then, we exploit the geometrical properties of the constraints and adopt an alternating manifold-based optimization to compute the optimal active beamformer and the RIS phase shifts, respectively. Simulation results demonstrate that the proposed RIS-assisted design significantly reduces the mutual interference and improves the system sum-rate for the communication system.

Original languageEnglish (US)
Pages (from-to)4909-4923
Number of pages15
JournalIEEE Transactions on Communications
Volume71
Issue number8
DOIs
StatePublished - Aug 1 2023
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • Integrated sensing and communications
  • interference mitigation
  • manifold optimization
  • reconfigurable intelligent surface
  • sum-rate maximization

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