Weighted Sum-Rate Maximization for RIS-Assisted MU-MIMO Communication Systems with Low-Resolution ADCs/DACs

Yingli Dong,Hui Li,Limeng Dong,Rui Liang, Ruonan Wang

2023 8th International Conference on Communication, Image and Signal Processing (CCISP)（2023）

School of Electronics and Information Northwestern Polytechnical University

Cited 1|Views3

Abstract

This paper focuses on maximizing the weighted sum-rate (WSR) in downlink communication systems that uti-lize reconfigurable intelligent surfaces (RIS) to enhance MU-MIMO transmission. To reduce implementation costs and power consumption, low-resolution ADCs/DACs are configured at the BS. Unlike the traditional design that predicated on perfect channel state information (CSI), we establish a WSR optimization problem given imperfect estimated CSI. Specifically, based on imperfect statistical CSI, we propose a robust weighted minimum mean square error (WMMSE) algorithm to maximize the beam-forming matrix, and then use riemann conjugate gradient (RCG) algorithm to optimize the phase shift vector with the aim of maximizing the WSR for all users. Numerical examples indicate that the proposed scheme improves system's robustness as well as achieves optimal WSR performance using three quantization bits.

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Key words

low-resolution ADCs/DACs,Reconfigurable Intelligent Surface (RIS),WSR,imperfect CSI,MU-MIMO

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Asymptotic Performance of Reconfigurable Intelligent Surface Assisted MIMO Communication for Large Systems Using Random Matrix Theory

Feng Hu, Hongliu Zhang, Shuting Chen,Libiao Jin, Jinhao Zhang,Yunfei Feng

IET COMMUNICATIONS 2024

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要点：本文提出了一种在利用可重构智能表面（RIS）增强多用户多输入多输出（MU-MIMO）传输的下行通信系统中，通过最大化加权和速率（WSR）来提高系统性能的方法。通过配置低分辨率ADCs/DACs来减少实施成本和功耗。与传统设计基于完美的信道状态信息（CSI）不同，我们考虑了有不完美的预估CSI的情况下，建立了一个WSR优化问题。具体来说，基于不完美的统计CSI，我们提出了一个鲁棒的加权最小均方误差（WMMSE）算法来最大化波束形成矩阵，并用Riemann共轭梯度（RCG）算法来优化相移矢量，以最大化所有用户的WSR。数值实验表明，所提出的方案提高了系统的鲁棒性，并在使用三位量化比特时实现了最优的WSR性能。

方法：基于不完美的统计CSI，提出鲁棒的WMMSE算法来最大化波束形成矩阵，然后使用RCG算法来优化相移矢量。

实验：通过数值实验，证明所提出的方案在使用三位量化比特时，能够提高系统的鲁棒性并实现最优的WSR性能。