Intelligent Reflecting Surfaces Beamforming Optimization with Statistical Channel Knowledge

Abstract

Intelligent Reflecting Surfaces (IRSs) are emerging as an effective technology capable of improving the spectral and energy efficiency of future wireless networks. The proposed scenario consists of a multi-antenna base station and a single-antenna user that is assisted by an IRS. The large number of reflecting elements at the IRS and its passive operation represent an important challenge in the acquisition of the instantaneous channel state information (I-CSI) of all links as it adds a very high overhead to the system and requires equipping the IRS with radio-frequency chains. To overcome this problem, a new approach is proposed in order to optimize beamforming at the BS and the phase shifts at the IRS without considering any knowledge of I-CSI but while only exploring the statistical channel state information (S-CSI). We aim at maximizing the user-achievable rate subject to a maximum transmit power constraint. To achieve this goal, we propose a new two-phase framework. In the first phase, both the beamforming at the BS and IRS are designed based only on S-CSI and, in the second phase, the previously designed beamforming pair is used as an initial solution, and beamforming at the BS and IRS is designed only by considering the feedback of the SNR at UE. Moreover, for each phase, we propose new methods based on Genetic Algorithms. Results show that the developed algorithms can approach beamforming with I-CSI but with significantly reduced channel estimation overhead.

A Robust Scheme for RIS-Assisted UAV Secure Communication in IoT

“…Figure 2 depicts the comparison of the proposed GA-TS and the conventional GA for convergence [31]. As shown, the population size was set as 30, 60 and 100, respectively.…”

“…Through a continuous iterative crossover and mutation, we could obtain the fittest individual that maximized the sum secrecy rate. Compared to traditional GA [31], a tabu search (TS) was introduced to accelerate the convergence speed of the algorithm. In each generation, the fittest individual gene of the population was recorded in the tabu table if the gene had not been recorded yet.…”

“…Moreover, a robust optimization problem was proposed to maximize the sum secrecy rate by jointly optimizing the transmit beamforming of BS and the reflect phase shift of RIS. In order to efficiently solve the proposed optimization problem, many heuristic methods were proposed, such as Genetic Algorithms (GA) [31], Particle Swarm Optimization [32] and Tabu Search [33]. In this study, we introduced the TS algorithm into the traditional GA algorithm.…”

A Survey on the Impact of Intelligent Surfaces in the Terahertz Communication Channel Models

“…RIS can generate a significant performance gain for the THz communication system. The large number of reflecting elements at the IRS and its passive operation represent essential challenges in beamforming design for THz due to its dependence on the accuracy of the estimated CSI, considering various degrees of CSI availability, namely imperfect CSI, partial CSI, and statistical CSI [ 36 ]. The beamforming design must be varied to minimize interference and enable robust communication [ 37 ].…”

Sum Rate Optimization of IRS-Aided Uplink Muliantenna NOMA with Practical Reflection

“…In doing so, the IRS avoids a large power consumption with passive elements and achieves a full-duplex gain without complicated signal processing such as interference cancellation and demodulation. In this aspect, various IRS-assisted wireless communications have been explored for their own purposes, from basic multiuser or/and multiantenna communication systems [4][5][6][7][8][9] to more complicated system configurations, as surveyed in Ref. [10].…”