Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design

Abstract

Millimeter wave (MmWave) communications is capable of supporting multi-gigabit wireless access thanks to its abundant spectrum resource. However, the severe path loss and high directivity make it vulnerable to blockage events, which can be frequent in indoor and dense urban environments. To address this issue, in this paper, we introduce intelligent reflecting surface (IRS) as a new technology to provide effective reflected paths to enhance coverage of mmWave signals. In this framework, we study joint active and passive precoding design for IRSassisted mmWave systems, where multiple IRSs are deployed to assist the data transmission from a base station (BS) to a single-antenna receiver. Our objective is to maximize the received signal power by jointly optimizing the transmit precoding vector at the BS and the phase shift parameters used by IRSs for passive beamforming. Although such an optimization problem is generally non-convex, we show that, by exploiting some important characteristics of mmWave channels, an optimal closed-form solution can be derived for the single IRS case and a nearoptimal analytical solution can be obtained for the multi-IRS case. Our analysis reveals that the received signal power increases quadratically with the number of reflecting elements for both the single IRS and multi-IRS cases. Simulation results are included to verify the optimality and near-optimality of our proposed solutions. Results also show that IRSs can help create effective virtual LOS paths and thus substantially improve robustness against blockages in mmWave communications.

mmWave Doubly-Massive-MIMO Communications Enhanced with an Intelligent Reflecting Surface

“…This paper has investigated a point-to-point IRSassisted mmWave doubly-massive MIMO system and derived expressions of the asymptotic sum rate when the numbers of antennas at the transmitter and receiver go to infinity. As a major difference compared to existing analysis and results, such [22] and [11], it is shown in this paper that the optimal solutions of power allocation, precoding/combining, and IRS's phase shifts for the doubly-massive MIMO system can be realized independently without the need of joint processing. Such solutions are very convenient for the system design.…”

“…We always fix L k 1 = L k 2 = L = 3. Other parameters are set as follows: P = 30 dBm and σ 2 n = −85 dBm [22]. Except for Fig.…”

“…To date, there are a few works that investigate IRS-aided mmWave MIMO systems for both single-user and multi-user scenarios, and with one or multiple IRSs. These works were concerned with rate optimization [19]- [21], joint active and passive beamforming design [22], [23], joint power allocation and beamforming design [24], hybrid beamforming design [25], [26], and channel estimation [27].…”

“…For a mmWave communication system, the severe path loss and high directivity make it vulnerable to blockage events, which can be frequent in indoor and dense urban environments [22]. Moreover, due to the multipath sparsity of mmWave signal propagation, the potential of spatial multiplexing is limited [8], [28].…”

Sum-Rate Maximization for Multi-Reconfigurable Intelligent Surface-Assisted Device-to-Device Communications

“…Most existing studies of RISs use the semidefinite relaxation (SDR) to solve quadratically constrained quadratic program (QCQP) problems formulated for the passive beamforming with a single constant-modulus constraint [24], [28], [29]. Unfortunately, the SDR would incur a prohibitive complexity if multiple RISs are involved or the RIS is large, due to the fact that the number of variables grows quadratically with the number of RIS elements.…”