Reconfigurable intelligent surface (RIS) has been anticipated to be a novel cost-effective technology to improve the performance of future wireless systems. In this paper, we investigate a practical RIS-aided multiple-input-multiple-output (MIMO) system in the presence of transceiver hardware impairments, RIS phase noise and imperfect channel state information (CSI). Joint design of the MIMO transceiver and RIS reflection matrix to minimize the total average mean-square-error (MSE) of all data streams is particularly considered. This joint design problem is non-convex and challenging to solve due to the newly considered practical imperfections. To tackle the issue, we first analyze the total average MSE by incorporating the impacts of the above system imperfections. Then, in order to handle the tightly coupled optimization variables and non-convex NP-hard constraints, an efficient iterative algorithm based on alternating optimization (AO) framework is proposed with guaranteed convergence, where each subproblem admits a closed-form optimal solution by leveraging the majorization-minimization (MM) technique. Moreover, via exploiting the special structure of the unit-modulus constraints, we propose a modified Riemannian gradient ascent (RGA) algorithm for the discrete RIS phase shift optimization. Furthermore, the optimality of the proposed algorithm is validated under line-of-sight (LoS) channel conditions, and the irreducible MSE floor effect induced by imperfections of both hardware and CSI is also revealed in the high signal-to-noise ratio (SNR) regime. Numerical results show the superior MSE performance of our proposed algorithm over the adopted benchmark schemes, and demonstrate that increasing the number of RIS elements is not always beneficial under the above system imperfections.
翻译:智能可重构面(RIS)被预期成为未来无线系统提高性能的一种新型、具有成本效益的技术。本文研究在收发机硬件失真、RIS相位噪声和非理想信道状态信息(CSI)存在的情况下的实际RIS辅助多输入多输出(MIMO)系统。具体考虑联合设计MIMO收发机和RIS反射矩阵,以最小化所有数据流的平均均方误差(MSE)。由于新考虑的实际失真,这个联合设计问题非凸,并且很难解决。为了解决这个问题,我们首先分析了考虑上述系统失真的总平均MSE。然后,为了处理紧密耦合的优化变量和非凸NP硬约束,提出了一种基于交替优化(AO)框架的高效迭代算法,其中每个子问题通过利用主副方差(MM)技术可以得到闭式最优解。此外,通过利用单元模数约束的特殊结构,我们提出了一种改进的里曼梯度上升(RGA)算法来优化离散RIS相移。此外,证明了所提出算法在直射(LoS)信道条件下的最优性,并揭示了由硬件和CSI失真引起的不可避免的MSE楼层效应在高信噪比(SNR)范围内。数值结果表明,我们提出的算法具有优越的MSE性能,超过了所采用的基准方案,并且表明在上述系统失真下增加RIS元素不总是有益的。