Robust Beamforming Design and Antenna Selection for Dynamic HRIS-aided Massive MIMO Systems

In this paper, a dynamic hybrid active-passive reconfigurable intelligent surface (HRIS) is proposed to further enhance the massive multiple-input-multiple-output (MIMO) system, since it supports the dynamic placement of active and passive elements. Specifically, considering the impact of the hardware impairments (HWIs), we investigate the channel-aware configuration of the receive antennas at the base station (BS) and the active/passive elements at the HRIS to improve the reliability of system. To this end, we investigate the average mean-square-error (MSE) minimization problem for the HRIS-aided massive MIMO system by jointly optimizing the BS receive antenna selection matrix, the reflection phase coefficients, the reflection amplitude matrix, and the mode selection matrix of the HRIS under the power budget of the HRIS. To tackle the non-convexity and intractability of this problem, we first transform the binary and discrete variables into continuous ones, and then propose a penalty-based exact block coordinate descent (BCD) algorithm to solve these subproblems alternately. Numerical simulations demonstrate the great superiority of the proposed scheme over the conventional benchmark schemes.

Joint Beamforming Optimization and Mode Selection for RDARS-aided MIMO Systems

Considering the appealing distribution gains of distributed antenna systems (DAS) and passive gains of reconfigurable intelligent surface (RIS), a flexible reconfigurable architecture called reconfigurable distributed antenna and reflecting surface (RDARS) is proposed. RDARS encompasses DAS and RIS as two special cases and maintains the advantages of distributed antennas while reducing the hardware cost by replacing some active antennas with low-cost passive reflecting surfaces. In this paper, we present a RDARS-aided uplink multi-user communication system and investigate the system transmission reliability with the newly proposed architecture. Specifically, in addition to the distribution gain and the reflection gain provided by the connection and reflection modes, respectively, we also consider the dynamic mode switching of each element which introduces an additional degree of freedom (DoF) and thus results in a selection gain. As such, we aim to minimize the total sum mean-square-error (MSE) of all data streams by jointly optimizing the receive beamforming matrix, the reflection phase shifts and the channel-aware placement of elements in the connection mode. To tackle this nonconvex problem with intractable binary and cardinality constraints, we propose an inexact block coordinate descent (BCD) based penalty dual decomposition (PDD) algorithm with the guaranteed convergence. Since the PDD algorithm usually suffers from high computational complexity, a low-complexity greedy-search-based alternating optimization (AO) algorithm is developed to yield a semi-closed-form solution with acceptable performance. Numerical results demonstrate the superiority of the proposed architecture compared to the conventional fully passive RIS or DAS. Furthermore, some insights about the practical implementation of RDARS are provided.

Reconfigurable Distributed Antennas and Reflecting Surface (RDARS): A New Architecture for Wireless Communications

Reconfigurable intelligent surfaces (RISs) have drawn much attention recently for their appealing advantages in shaping wireless channels to improve the spectral and energy efficiencies of wireless communications. However, conventional fully-passive RISs generally suffer from the so-called ``multiplicative fading'' effect which thereby limits RISs' practicability and manufacturability. In this paper, a novel architecture of ``Reconfigurable Distributed Antennas and Reflecting Surfaces (RDARS)'' is first proposed to overcome this limitation from the ``multiplicative fading'' effect. Specifically, unlike existing active RIS variants, RDARS inherits the low-cost and low-energy-consumption benefits of fully-passive RISs by default configuring all the elements as passive to perform the reflection mode. On the other hand, based on the design of the additional direct-through state, any element of the RDARS can be dynamically programmed to connect with the base station (BS) via fibers and perform the connected mode as remote distributed antennas of the BS to receive signals. Consequently, a controllable trade-off between the reflection gain and the distribution gain can be achieved via RDARS at the BS. To unveil the system behavior of the RDARS-aided system, we analyze the received signal-to-noise ratio (SNR) under maximum ratio combining (MRC) at BS. Closed-form outage probability and ergodic achievable rate are also provided and are verified through extensive simulations. To demonstrate the superiority of the proposed RDARS, experiments are carried out using a prototype of RDARS with a total number of 256 elements which revealed extra 76% throughput improvement could be achieved by deploying RDARS with only three elements performing connected mode. This thus confirms the effectiveness of the proposed RDARS and envisions it as a promising candidate for future 6G wireless systems.