ﻻ يوجد ملخص باللغة العربية
Intelligent reflecting surface (IRS) has drawn a lot of attention recently as a promising new solution to achieve high spectral and energy efficiency for future wireless networks. By utilizing massive low-cost passive reflecting elements, the wireless propagation environment becomes controllable and thus can be made favorable for improving the communication performance. Prior works on IRS mainly rely on the instantaneous channel state information (I-CSI), which, however, is practically difficult to obtain for IRS-associated links due to its passive operation and large number of elements. To overcome this difficulty, we propose in this paper a new two-timescale (TTS) transmission protocol to maximize the achievable average sum-rate for an IRS-aided multiuser system under the general correlated Rician channel model. Specifically, the passive IRS phase-shifts are first optimized based on the statistical CSI (S-CSI) of all links, which varies much slowly as compared to their I-CSI, while the transmit beamforming/precoding vectors at the access point (AP) are then designed to cater to the I-CSI of the users effective channels with the optimized IRS phase-shifts, thus significantly reducing the channel training overhead and passive beamforming complexity over the existing schemes based on the I-CSI of all channels. For the single-user case, a novel penalty dual decomposition (PDD)-based algorithm is proposed, where the IRS phase-shifts are updated in parallel to reduce the computational time. For the multiuser case, we propose a general TTS optimization algorithm by constructing a quadratic surrogate of the objective function, which cannot be explicitly expressed in closed-form. Simulation results are presented to validate the effectiveness of our proposed algorithms and evaluate the impact of S-CSI and channel correlation on the system performance.
Intelligent reflecting surface (IRS) is an emerging technology that is able to reconfigure the wireless channel via tunable passive signal reflection and thereby enhance the spectral and energy efficiency of wireless networks cost-effectively. In thi
In intelligent reflecting surface (IRS) aided wireless communication systems, channel state information (CSI) is crucial to achieve its promising passive beamforming gains. However, CSI errors are inevitable in practice and generally correlated over
The performance of a device-to-device (D2D) underlay communication system is limited by the co-channel interference between cellular users (CUs) and D2D devices. To address this challenge, an intelligent reflecting surface (IRS) aided D2D underlay sy
Intelligent reflecting surface (IRS) is a promising technology for wireless communications, thanks to its potential capability to engineer the radio environment. However, in practice, such an envisaged benefit is attainable only when the passive IRS
In this paper, the minimum mean square error (MMSE) channel estimation for intelligent reflecting surface (IRS) assisted wireless communication systems is investigated. In the considered setting, each row vector of the equivalent channel matrix from