Despite the appealing advantages of reconfigurable intelligent surfaces (RIS) aided mmWave communications, there remain practical issues that need to be addressed before the large-scale deployment of RISs in future wireless networks. In this study, we jointly consider the non-neglectable practical issues in a multi-RIS-aided mmWave system, which can significantly affect the secrecy performance, including the high computational complexity, imperfect channel state information (CSI), and finite resolution of phase shifters. To solve this non-convex challenging stochastic optimization problem, we propose a robust and low-complexity algorithm to maximize the achievable secrete rate. Specially, by combining the benefits of fractional programming and the stochastic successive convex approximation techniques, we transform the joint optimization problem into some convex ones and solve them sub-optimally. The theoretical analysis and simulation results demonstrate that the proposed algorithms could mitigate the joint negative effects of practical issues and yielded a tradeoff between secure performance and complexity/overhead outperforming non-robust benchmarks, which increases the robustness and flexibility of multiple RIS deployments in future wireless networks.

In this paper, the uplink performance of Multi-User Multiple Input Multiple Output (MU-MIMO) Zero Forcing (ZF) receiver is investigated over correlated Rayleigh fading channels with channel estimation error. A mathematical expression for the sub-streams' output Signal to Noise Ratio (SNR) with transmit and receive-correlation is derived in the presence of erroneous channel estimates. Besides, an approximate and accurate expression for the Bit Error Rate (BER) of ZF receiver for 16-Quadrature Amplitude Modulation (QAM) with transmit-correlation is deduced in terms of the hypergeometric function. Subsequently, the developed analytical BER is verified by Monte-Carlo trails accounting various system parameters. The simulation results indicate that ZF receiver's BER relies solely on the transmit-correlation for the same number of transmit and receive-antennas at higher average SNR values per transmitted symbol (Es/N0). Also, a logarithmic and exponential growth in the BER is observed with an increase in the Mean Square estimation Error (MSE) and correlation coefficient, respectively.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.

We study the transmission techniques in orthogonal frequency division multiplexing (OFDM) systems with imperfect channel state information at the transmitter (CSIT). We focus on the issue of utilizing the available CSIT by a single forward error control (FEC) code. We first analyze the system performance for the ideal coding case. We then develop a simple but efficient scheme for the practical coding case, which is based on joint FEC coding and linear precoding at the transmitter and iterative linear minimum-mean-square-error (LMMSE) detection at the receiver. Numerical results show that significant performances gains can be achieved by the proposed scheme.

In a closed-loop scenario, the performance of transmit-diversity schemes for a multiple antenna system depends on the reliability of the channel state information (CSI). However, estimating the reliability of the instantaneous CSI at the transmitter is a challenging task. In this paper, we propose a robust transmit-diversity scheme for the case when the instantaneous CSI available at the transmitter is imperfect and its reliability is unknown to the transmitter. We show by simulation that our proposed scheme is efficient when the CSI reliability varies arbitrarily in every channel realization.

In this paper we investigate designing optimal linear transmit/receive processing filters for multiuser MIMO downlinks with imperfect channel state information (CSI) and spatial fading correlation between antenna array at BS. A robust scheme is proposed to obtain the optimal linear transmit/receive filters in the sense of minimizing the average sum mean square error (SMSE) conditional on noisy channel estimates under a per-user transmit power constraint. Using an iterative procedure, the proposed scheme extends the existing optimization algorithm for uncorrelated single-user MIMO systems with perfect CSI to solve the problem of minimizing SMSE in spatially correlated MIMO downlinks with imperfect CSI. Comparing with non-robust scheme, we show that robust scheme efficiently mitigates the BER loss induced by imperfect CSI. In addition, the impact of fading correlation at BS on the performance of the proposed robust scheme is analyzed.

This paper proposes a new minimum BER (MBER) criterion precoding method that is robust to imperfect channel state information (CSI) for MIMO-OFDM mobile communications. The proposed MBER precoding aims to minimize BER of the maximum likelihood detection (MLD), on the condition that the transmitter can obtain only imperfect CSI owing to channel estimation and quantization errors of the feedback CSI. The proposed scheme controls its precoding parameters under a transmit power constraint by minimizing an upper bound of BER which is derived from the pairwise error probability and averaged with respect to the CSI error. In contrast with a conventional power allocation MBER precoding method that is also robust to the CSI error, the proposed scheme does not make any assumption on the precoding parameters so as to reduce complexity. Thus, it is expected to outperform the conventional scheme at the cost of higher complexity. Computer simulations demonstrate that the proposed precoding method outperforms a conventional nonrobust MBER precoder and the conventional robust power allocation MBER precoding method when the amount of the CSI error is not considerable.