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DRL-based Joint Beamforming and Power Allocation in Beyond Diagonal Reconfigurable Intelligence Surface 6G Systems
Mousa Abdollahvand , Sima Sobhi-givi
Abstract:   (283 Views)
This paper introduces a new method for improving wireless communication systems by employing beyond diagonal reconfigurable intelligent surfaces (BD-RIS) and unmanned aerial vehicle (UAV) alongside deep reinforcement learning (DRL) techniques. BD-RIS represents a departure from traditional RIS designs, providing advanced capabilities for manipulating electromagnetic waves to optimize the performance of communication. We propose a DRL-based framework for optimizing the UAV and configuration of BD-RIS elements, including hybrid beamforming, phase shift adjustments, and transmit power coefficients for non-orthogonal multiple access (NOMA) transmission by considering max-min fairness. Through extensive simulations and performance evaluations, we demonstrate that BD-RIS outperforms conventional RIS architectures. Additionally, we analyze the convergence speed and performance trade-offs of different DRL algorithms, emphasizing the importance of selecting the appropriate algorithm and hyper-parameters for specific applications. Our findings underscore the transformative potential of BD-RIS and DRL in enhancing wireless communication systems, laying the groundwork for next-generation network optimization and deployment.
Keywords: Unmanned aerial vehicle (UAV), beyond diagonal-reconfigurable intelligent surface (BD-RIS), Non-orthogonal multiple access (NOMA), hybrid beamforming, reinforcement learning (RL).
Full-Text [PDF 730 kb]   (74 Downloads)    
Type of Study: Research Paper | Subject: Communication Systems
Received: 2024/05/29 | Revised: 2024/11/01 | Accepted: 2024/10/31
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.