Robust Transmission Design for RIS-Assisted Integrated Sensing and Communication Systems

As a critical technology for next-generation communication networks, integrated sensing and communication (ISAC) aims to achieve the harmonious coexistence of communication and sensing. The degrees-of-freedom (DoF) of ISAC is limited due to multiple performance metrics used for communication and sen...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 73; no. 11; pp. 17151 - 17164
Main Authors: Xu, Yongqing, Li, Yong, Quek, Tony Q.S.
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Approximation algorithms
Array signal processing
Beamforming
Communication
Communication networks
Communications systems
Convergence
Cramer-Rao bounds
Degrees of freedom
Error analysis
Integrated sensing and communication
intelligent reflecting surfaces
Interference
joint communication and sensing
Metamaterials
Performance measurement
Radar
Receiving antennas
Reconfigurable intelligent surfaces
robust beamforming design
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:As a critical technology for next-generation communication networks, integrated sensing and communication (ISAC) aims to achieve the harmonious coexistence of communication and sensing. The degrees-of-freedom (DoF) of ISAC is limited due to multiple performance metrics used for communication and sensing. Reconfigurable Intelligent Surfaces (RIS) composed of metamaterials can enhance the DoF in the spatial domain of ISAC systems. However, the availability of perfect Channel State Information (CSI) is a prerequisite for the gain brought by RIS, which is not realistic in practical environments. Therefore, under the imperfect CSI condition, we propose a decomposition-based large deviation inequality approach to eliminate the impact of CSI error on communication rate and sensing Cramér-Rao bound (CRB). Then, an alternating optimization (AO) algorithm based on semi-definite relaxation (SDR) and gradient extrapolated majorization-maximization (GEMM) is proposed to solve the transmit beamforming and discrete RIS beamforming problems. We also analyze the complexity and convergence of the proposed algorithm. Simulation results show that the proposed algorithms can effectively eliminate the influence of CSI error and have good convergence performance. Notably, when CSI error exists, the gain brought by RIS will decrease with the increase of the number of RIS elements.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2024.3426042