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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.09149 |
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| _version_ | 1866909169361092608 |
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| author | Yan, Bai Zhao, Qi Zhang, Jin Zhang, J. Andrew |
| author_facet | Yan, Bai Zhao, Qi Zhang, Jin Zhang, J. Andrew |
| contents | This paper tackles the deployment challenges of Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS) in communication systems. Unlike existing works that use fixed deployment setups or solely optimize the location, this paper emphasizes the joint optimization of the location and orientation of STAR-RIS. This enables searching across all user grouping possibilities and fully boosting the system's performance. We consider a sum rate maximization problem with joint optimization and hybrid beamforming design. An offline heuristic solution is proposed for the problem, developed based on differential evolution and semi-definite programming methods. In particular, a point-point representation is proposed for characterizing and exploiting the user-grouping. A balanced grouping method is designed to achieve a desired user grouping with low complexity. Numerical results demonstrate the substantial performance gains achievable through optimal deployment design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_09149 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Heuristic Solution to Joint Deployment and Beamforming Design for STAR-RIS Aided Networks Yan, Bai Zhao, Qi Zhang, Jin Zhang, J. Andrew Systems and Control Numerical Analysis Neural and Evolutionary Computing This paper tackles the deployment challenges of Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS) in communication systems. Unlike existing works that use fixed deployment setups or solely optimize the location, this paper emphasizes the joint optimization of the location and orientation of STAR-RIS. This enables searching across all user grouping possibilities and fully boosting the system's performance. We consider a sum rate maximization problem with joint optimization and hybrid beamforming design. An offline heuristic solution is proposed for the problem, developed based on differential evolution and semi-definite programming methods. In particular, a point-point representation is proposed for characterizing and exploiting the user-grouping. A balanced grouping method is designed to achieve a desired user grouping with low complexity. Numerical results demonstrate the substantial performance gains achievable through optimal deployment design. |
| title | Heuristic Solution to Joint Deployment and Beamforming Design for STAR-RIS Aided Networks |
| topic | Systems and Control Numerical Analysis Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2404.09149 |