基于可重构智能曲面的近场MIMO信道空间复用

G. Bartoli, A. Abrardo, Nicoló Decarli, D. Dardari, M. D. Renzo
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引用次数: 12

摘要

我们考虑了在可重构智能表面(RIS)存在下的多输入多输出(MIMO)通道。具体来说,我们的重点是分析近场视距和低散射MIMO信道的空间复用增益。通过对角化端到端发送端- ris -接收端信道,并对发送端- ris和ris -接收端信道奇异值的有序积应用充水功率分配,证明了信道容量的实现。所得的容量实现解需要RIS具有反射系数的非对角矩阵。在近无源RIS的假设下,即RIS处不需要功率放大,则只需要在发射机处进行充水功率分配。我们将RIS的这种设计称为线性、几乎无源、可重构的电磁对象(EMO)。此外,我们还介绍了RIS的一种封闭形式和低复杂度设计,其反射系数矩阵是对角的,具有单位模项。反射系数由两个聚焦函数的乘积给出:一个聚焦函数将ris辅助信号指向MIMO发射器的中点,另一个聚焦函数将ris辅助信号指向MIMO接收器的中点。我们证明了该解在近轴设置下的视距通道中是精确的。借助视距(自由空间)通道中的大量数值模拟,我们表明所提出的方法提供的性能(速率和自由度)接近于在高计算复杂度下通过数值解决非凸优化问题获得的性能。此外,我们还表明,在大多数考虑的案例研究中,它提供的性能接近EMO(非对角RIS)所达到的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Multiplexing in Near Field MIMO Channels with Reconfigurable Intelligent Surfaces
We consider a multiple-input multiple-output (MIMO) channel in the presence of a reconfigurable intelligent surface (RIS). Specifically, our focus is on analyzing the spatial multiplexing gains in line-of-sight and low-scattering MIMO channels in the near field. We prove that the channel capacity is achieved by diagonalizing the end-to-end transmitter-RIS-receiver channel, and applying the water-filling power allocation to the ordered product of the singular values of the transmitter-RIS and RIS-receiver channels. The obtained capacity-achieving solution requires an RIS with a non-diagonal matrix of reflection coefficients. Under the assumption of nearly-passive RIS, i.e., no power amplification is needed at the RIS, the water-filling power allocation is necessary only at the transmitter. We refer to this design of RIS as a linear, nearly-passive, reconfigurable electromagnetic object (EMO). In addition, we introduce a closed-form and low-complexity design for RIS, whose matrix of reflection coefficients is diagonal with unit-modulus entries. The reflection coefficients are given by the product of two focusing functions: one steering the RIS-aided signal towards the mid-point of the MIMO transmitter and one steering the RIS-aided signal towards the mid-point of the MIMO receiver. We prove that this solution is exact in line-of-sight channels under the paraxial setup. With the aid of extensive numerical simulations in line-of-sight (free-space) channels, we show that the proposed approach offers performance (rate and degrees of freedom) close to that obtained by numerically solving non-convex optimization problems at a high computational complexity. Also, we show that it provides performance close to that achieved by the EMO (non-diagonal RIS) in most of the considered case studies.
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