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Max-min rate optimization for multi-user MISO-OFDM systems assisted by RIS with a wideband model

Author(s): Yonghua QUAN, Zhong TIAN, Zhengchuan CHEN, Min WANG, Yunjian JIA
Affiliation(s): School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China; more
Corresponding email(s): qyh@cqu.edu.cn, ztian@cqu.edu.cn, czc@cqu.edu.cn
Key Words: Reconfigurable intelligent surface; Max-min rate; Coalition-game subcarrier allocation

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Abstract: Reconfigurable intelligent surfaces (RISs) have the capability to change the wireless environment smartly. Considering the attenuation of subchannels and crowding users involved in the wideband system, we introduce RISs into the multi-user multi-input single-output (MU-MISO) system with orthogonal frequency division multiplexing (OFDM) for performance enhancement. Maximizing the minimum rate of dense users in an MU-MISO-OFDM system assisted by RIS with an approximate practical model is formulated as the joint optimization problem involving subcarrier allocation, transmit precoding (TPC) matrices at the base station, and RIS passive beamforming. A coalition-game subcarrier allocation (CSA) algorithm is proposed to solve space–frequency resource allocation on subcarriers, which reforms the interference topology among dense users. Fractional programming and convex optimization method are used to optimize the TPC matrices and the RIS passive beamforming, which improves the spectral efficiency synthetically across all subchannels in the wideband system. Simulation results indicate that the CSA algorithm provides a significant gain for dense users. Besides, the proposed joint optimization method shows the considerable advantage of the RISs in the MU-MISO-OFDM system.

基于智能超表面宽带模型的下行多用户MISO-OFDM系统最大化最小速率优化

全永桦¹，田中¹，陈正川^1,2，王敏^3,4，贾云健¹
¹重庆大学微电子与通信工程学院，中国重庆市，400044
²西安邮电大学陕西省信息通信网络及安全重点实验室，中国西安市，710121
³重庆邮电大学光电工程学院，中国重庆市，400065
⁴桂林电子科技大学广西无线宽带通信与信号处理重点实验室，中国桂林市，541004
摘要：智能超表面具有智能化改变无线环境的能力。考虑到宽带系统中子信道的衰减和拥挤的用户，我们将智能超表面引入具有正交频分复用（orthogonal frequency division multiplexing,OFDM）的多用户多入单出（multi-input single-output,MISO）系统，用于增强系统性能。基于智能超表面的近似实用宽带模型，智能超表面辅助密集用户的最小速率最大化问题被表征为包含子载波分配、基站发送预编码矩阵和智能超表面无源波束形成的联合优化问题。提出联盟博弈子载波分配算法解决子载波的空频资源分配问题，改善密集用户间的干扰拓扑。利用分数规划和凸优化方法优化预编码矩阵和智能超表面无源波束形成，提高了宽带系统中所有子信道的频谱效率。仿真结果表明，联盟博弈子载波分配算法为密集用户提供了显著的速率增益。此外，所提联合优化方法展示了智能超表面在该系统中的显著优势。

关键词组：智能超表面；最大化最小速率；联盟博弈子载波分配

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基于智能超表面宽带模型的下行多用户MISO-OFDM系统最大化最小速率优化

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