Intelligent reflecting surface (IRS) is an emerging technology that able to reconfigure the wireless channel via tunable passive signal reflection and thereby enhance spectral energy efficiency of networks cost-effectively. In this paper, we study IRS-aided multiuser multiple-input single-output (MISO) system adopt two-timescale (TTS) transmission reduce processing complexity training overhead ...

Intelligent reflecting surface (IRS) is envisioned as a promising hardware solution to cost and energy consumption in the fifth-generation (5G) mobile communication network. It exhibits great advantages enhancing data transmission, but may suffer from performance degradation caused by inherent impairment (HWI). For analysing achievable rate (ACR) optimizing phase shifts IRS-aided wireless syste...

In this letter, the downlink transmission of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) system is investigated where IRS elements are selected from a predefined discrete set phase shifts. We minimize mean square error (MSE) received symbols in via optimizing shifts at jointly with beamforming vectors base station (BS) and equalizers user terminals. orde...

Intelligent reflecting surface (IRS), which consists of a large number tunable reflective elements, is capable enhancing the wireless propagation environment in cellular network by intelligently electromagnetic waves from base-station (BS) toward users. The optimal tuning phase shifters at IRS is, however, challenging problem, because due to passive nature it difficult directly measure channels...

Channel estimation is one of the main tasks in realizing practical intelligent reflecting surface-assisted multi-user communication (IRS-MUC) systems. However, different from traditional systems, an IRS-MUC system generally involves a cascaded channel with sophisticated statistical distribution. In this case, optimal minimum mean square error (MMSE) estimator requires calculation multidimension...

In this paper, the problem of maximizing sum data rates all users in an intelligent reflecting surface (IRS)-assisted millimeter wave multicast multiple-input multiple-output communication system is studied. considered model, one IRS deployed to assist from a multi-antenna base station (BS) that are clustered into several groups. Our goal maximize rate by jointly optimizing transmit beamforming...

Intelligent reflecting surface (IRS) has emerged as a cost-efficient technique to improve the wireless network’s capacity and performance. Existing works on IRS have mainly considered being deployed in environment dynamically control channels between base station (BS) its served users favor of their communications. In contrast, we propose this paper new integrated IRS-BS architecture by deployi...

Intelligent reflecting surface (IRS) is envisioned as a revolutionary technology for future wireless communication systems since it can intelligently change radio environment and integrate into optimization. However, most existing works adopted an ideal IRS reflection model, which impractical cause significant performance degradation in realistic wideband systems. To address this issue, we firs...

Driven by the emergence of promising Internet-of-Everything (IoE) applications ranging from extended reality and automated systems to tactile Internet, 6G is expected provide diverse services including, e.g., communication, computing, sensing, as well achieve more ambitious network performance than 5G. To meet future demands 6G, an innovative concept referred <italic xmlns:mml="http://www.w3.or...

This article introduces a neural network-based signal processing framework for intelligent Reflecting surface-aided (IRS) wireless communications systems. By modeling radio frequency (RF) impairments inside the meta-atoms of IRS - including nonlinearity and memory effects) we present an approach that generalizes entire IRS-aided system as reservoir computing (RC) system, efficient recurrent net...