Performance Optimization for Environment-Aware STAR-RIS Assisted TeraHertz Multi-User Ultra-Massive MIMO Systems Based on Microwave Coincidence Imaging

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Terahertz</i> (THz) systems can accommodate extremely high data rates thanks to large bandwidth. However, the sensitivity to blockages is a key challenge for THz signals, and even user position variation may cause misalignment of THz pencil-like beamforming resulting in sharp decline in system performance. In this paper, we propose a novel system performance optimization scheme for environment-aware <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface</i> (STAR RIS) assisted THz multi-user ultra-massive MIMO systems with information of environmental obstacles such as geometry and spatial layout taken into account for the first time. We resort to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Integrated Sensing and Communication</i> (ISAC) technique and propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Microwave Coincidence Imaging</i> (MCI) based beamforming and optimization scheme, which can adapt to environmental and user position variation. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cloud radio access networks</i> (CRAN) structured 5G downlink signal is proposed for MCI with much enhanced resolution. We first conduct MCI to obtain 3D images of the environment including users and obstacles, based on which we calculate the optimal position of the STAR by the proposed algorithm. We further combine with channel estimation and propose a semi-passive structure of the STAR and ambiguity elimination scheme for separated channel estimation. Simulation results show that the proposed scheme increases the system performance dramatically compared to the benchmark and the case when the STAR operates with random phases. Furthermore, the proposed scheme improves the system performance on average by 14.26%, 18.35% and 60.60% for three different configurations compared to that at the 10% deviation from the optimal position of the STAR even with perfect <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">channel state information</i> (CSI).

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Journal
IEEE Transactions on Vehicular Technology
Published
2025-04-01
DOI
https://doi.org/10.1109/tvt.2025.3551739
Primary Topic
Antenna Design and Optimization
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article
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article

Performance Optimization for Environment-Aware STAR-RIS Assisted TeraHertz Multi-User Ultra-Massive MIMO Systems Based on Microwave Coincidence Imaging

Pei Xiao, Zihuai Lin, Feng Lin, Xufang Wang
IEEE Transactions on Vehicular Technology
Antenna Design and Optimization
article

Performance Optimization for Environment-Aware STAR-RIS Assisted TeraHertz Multi-User Ultra-Massive MIMO Systems Based on Microwave Coincidence Imaging

Pei Xiao, Zihuai Lin, Feng Lin, Xufang Wang
article en

Abstract

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Terahertz</i> (THz) systems can accommodate extremely high data rates thanks to large bandwidth. However, the sensitivity to blockages is a key challenge for THz signals, and even user position variation may cause misalignment of THz pencil-like beamforming resulting in sharp decline in system performance. In this paper, we propose a novel system performance optimization scheme for environment-aware <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface</i> (STAR RIS) assisted THz multi-user ultra-massive MIMO systems with information of environmental obstacles such as geometry and spatial layout taken into account for the first time. We resort to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Integrated Sensing and Communication</i> (ISAC) technique and propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Microwave Coincidence Imaging</i> (MCI) based beamforming and optimization scheme, which can adapt to environmental and user position variation. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cloud radio access networks</i> (CRAN) structured 5G downlink signal is proposed for MCI with much enhanced resolution. We first conduct MCI to obtain 3D images of the environment including users and obstacles, based on which we calculate the optimal position of the STAR by the proposed algorithm. We further combine with channel estimation and propose a semi-passive structure of the STAR and ambiguity elimination scheme for separated channel estimation. Simulation results show that the proposed scheme increases the system performance dramatically compared to the benchmark and the case when the STAR operates with random phases. Furthermore, the proposed scheme improves the system performance on average by 14.26%, 18.35% and 60.60% for three different configurations compared to that at the 10% deviation from the optimal position of the STAR even with perfect <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">channel state information</i> (CSI).

IEEE Transactions on Vehicular TechnologyVol. 74(8)
Fujian Normal University (CN), The University of Sydney (AU), University of Surrey (GB), Digital Science (United States) (US), Xiamen University of Technology (CN)
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Antenna Design and Optimization
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