Joint Beamforming and Channel Reconfiguration for RIS-Assisted Millimeter Wave Massive MIMO-OFDM Systems
Joint Beamforming and Channel Reconfiguration for RIS-Assisted Millimeter Wave Massive MIMO-OFDM Systems
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DOI：
10.1109/tvt.2023.3243389
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发表时间：
2023-06
影响因子：
6.8
通讯作者：
Hanyu Wang;Jun Fang;Hongbin Li
中科院分区：
文献类型：
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作者：
Hanyu Wang;Jun Fang;Hongbin Li
本文研究了可重构智能表面（RIS）辅助毫米波（mmWave）多输入多输出（MIMO）正交频分复用（OFDM）系统的联合主动和被动波束形成问题。目标是通过联合优化RIS反射系数和基站/移动站混合预编码器/合并器，实现频谱效率最大化。利用经典的预编码器/组合器混合优化技术，可以将联合波束形成问题转化为只考虑反射系数设计的优化问题。然而，由此产生的被动波束形成问题的目标函数并没有反射系数的显式表达式。为了解决这一难题，利用有效信道的固有结构，在此基础上得到有效信道截断奇异值分解（SVD）的近似，并通过直接操纵有效信道的奇异值来实现良好的传播环境。仿真结果表明，该方法能够以较小的条件数配置有利信道。此外，该方法在计算复杂度较低的情况下，与现有算法相比具有明显的性能优势。
In this paper, we consider the problem of joint active and passive beamforming for reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The objective is to maximize the spectral efficiency by jointly optimizing the RIS's reflection coefficients and the hybrid precoder/combiner at the base station (BS)/mobile station (MS). By resorting to classical hybrid precoder/combiner optimization techniques, this joint beamforming problem can be converted into an optimization concerning only the design of the reflection coefficients. Nevertheless, the objective function of the resulting passive beamforming problem does not have an explicit expression of the reflection coefficients. To address this difficulty, the inherent structure of the effective channel is exploited, based on which an approximation of the truncated singular value decomposition (SVD) of the effective channel is obtained, and a favorable propagation environment can be realized by directly manipulating the singular values of the effective channel. Simulation results show that the proposed method can configure a favorable channel with a small condition number. Moreover, the proposed method presents a clear performance advantage over state-of-the-art algorithms, while with a low computational complexity.