Intelligent reflecting surface (IRS) has emerged as a promising and low-cost technology for improving wireless communications by collecting dispersed radio waves and redirecting them to the intended receivers. In this letter, we characterize the achievable rate when multiple IRSs are utilized in the manner of decode-and-forward (DF) relaying. Our performance analysis is based on the Nakagami-m fading model with perfect channel state information (CSI). Tight upper bound expressions for the ergodic rate are derived. Moreover, we compare the performance of the multi-IRS DF relaying system with that of the one with a single IRS and confirm the gain. We then optimize the IRS configuration considering the numbers of IRSs and IRS reflecting elements, which provides useful insights for practical design.

Cell-free massive distributed antenna system (CF-MDAS) can further reduce the access distance between mobile stations (MSs) and remote access points (RAPs), which brings a lower propagation loss and higher multiplexing gain. However, the interference caused by the overlapping coverage areas of distributed RAPs will severely degrade the system performance in terms of the sum-rate. Since that clustering RAPs can mitigate the interference, in this paper, we investigate a novel clustering algorithm for a downlink CF-MDAS with the limited-capacity backhaul. To reduce the backhaul burden and mitigate interference effectively, a semidynamic bidirectional clustering algorithm based on the long-term channel state information (CSI) is proposed, which has a low computational complexity. Simulation results show that the proposed algorithm can efficiently achieve a higher sum-rate than that of the static clustering one, which is close to the curve obtained by dynamic clustering algorithm using the short-term CSI. Furthermore, the proposed algorithm always reveals a significant performance gain regardless of the size of the networks.

Intelligent reflecting surface (IRS) is regarded as a promising emerging technology, which has shown enormous potentials for performance enhancement. This paper investigates the multiple IRS-aided dual-hop DF relaying system for both single-user and multi-user scenarios over Nakagami-m fading. Based on a scenario with non-orthogonal multiple access users, tight upper bounds for the ergodic capacity in perfect channel state information(pCSI) scenario are first derived, and then approximate expressions are obtained in imperfect CSI (ipCSI) mode. Moreover, the performance of multiple IRS-aided DF relaying system are compared with multi-IRSs-only system and DF relaying-only system. Finally, all the analytical results are verified using Monte Carlo simulations. INTRODUCTIONRecently, with the rapid growth of data traffic over wireless networks, more and more attention are attracted to spectrum, energy and cost efficient design for the future sixth-generation (6G). Intelligent reflecting surface (IRS) technology has been newly proposed as a promising emerging solution to enhance the performance of wireless communication networks from various aspects such as coverage extension, capacity enlargement, and secrecy improvement by artificially reconfiguring the propagation environment of electromagnetic waves [1-3]. Compared to the conventional active relays supporting massive multiple input multiple-output (MIMO) systems [4], a typical IRS does not need decode or amplify, which contains a large number of passive reflecting elements. By contrast, it simply reflects the incident signals toward one or multiple desired directions by designing its amplitudes and phase-shifts [5]. Thus, IRS can improve spectrum efficiency, decrease energy consumption and enhance wireless physical layer security [6-8].Considerable efforts have been made to study the IRSassisted wireless communication in recent years. For example, symbol error probability (SEP) for both intelligent and random phase adjustments at the IRS reflectors is analytically investigated in ref. [9], besides, it confirms that an increase of reflective elements on the IRS has a significantly positive impact onThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.