Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)

2020

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/energy efficiency of wireless networks cost-effectively. In this paper, we study an IRS-aided multiuser multiple-input single-output (MISO) wireless system and adopt the two-timescale (TTS) transmission to reduce the signal processing complexity and channel training overhead as compared to the existing schemes based on the instantaneous channel state information (I-CSI), and at the same time, exploit the multiuser channel diversity in transmission scheduling. Specifically, the long-term passive beamforming (i.e., IRS phase shifts) is designed based on the statistical CSI (S-CSI) of all links, while the short-term active beamforming (i.e., transmit precoding vectors at the access point (AP)) is designed to cater to the I-CSI of all users' reconfigured channels with optimized IRS phase shifts. We aim to minimize the average transmit power at the AP, subject to the users' individual quality of service (QoS) constraints on the achievable long-term average rate. The formulated stochastic optimization problem is nonconvex and difficult to solve since the long-term and short-term design variables are complicatedly coupled in the QoS constraints. To tackle this problem, we propose an efficient algorithm, called the primal-dual decomposition based TTS joint active and passive beamforming (PDD-TJAPB), where the original problem is decomposed into a long-term passive beamforming problem and a family of shortterm active beamforming problems, and the deep unfolding technique is employed to extract gradient information from the short-term problems to construct a convex surrogate problem for the long-term problem. We show that both the long-term and short-term problems can be efficiently solved and the proposed algorithm is proved to converge to a stationary solution of the original problem almost surely. Simulation results are presented which demonstrate the advantages and effectiveness of the proposed algorithm as compared to benchmark schemes.

Section: Simulation Resultsmentioning

confidence: 99%

Two-timescale Beamforming Optimization for Intelligent Reflecting Surface Enhanced Wireless Network

Zhao

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)

2020

“…As shown in Fig. 2, the coordinate of the AP is (0, 0, 0) and it is assumed that three IRSs are located at (0, 20, 20), (0, 40,20) and (0, 60, 20) in meters, respectively. While user and eavesdropper are located at (0, 20, 0), and (0, 40, 0) in meters, respectively.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…We compare the proposed distributed IRSs-aided scheme with the single IRS-aided scheme and the all active IRSs-aided scheme (i.e., distributed IRSs-aided scheme without the switch). In the single IRS-aided scheme, the IRS locates at (0, 40,20) in meters, where the number of reflecting elements of the IRS is set as the total number of reflecting elements for all IRSs in the distributed IRSs-aided scheme. Moreover, we compare the proposed algorithm with the following three benchmark algorithms:…”

Section: Numerical Resultsmentioning

confidence: 99%

Wireless Secure Signal Transmission for Distributed Intelligent Surface-Aided Millimeter Wave Systems

Xiu

2020

IEEE Access

The optimization of the secrecy rate of the distributed intelligent reflecting surfaces (IRSs)assisted millimeter wave (mmWave) communication system is studied in this paper. In this system, the users are served by multiple IRSs, and by adjusting the switch state of each IRS and optimizing the phase shift of the IRS to maximize the secrecy rate of the system. The problem is described as a joint IRS control, transmit beamforming design problem. Our objective is to maximize the secrecy rate of the distributed IRSs-aided system under the transmit power constraint of the access point (AP). Since the problem is nonconvex, one alternating optimization algorithm is proposed for solving this problem. We use the successive convex approximation (SCA) algorithm to solve it, and the solution that is obtained by the SCA algorithm guarantees to converge to a stable point that satisfies the Karush-Kuhn-Tucker (KKT) conditions. Moreover, by using the dual method, we obtain the IRS switch. For the IRS phase shifts optimization problem, a lowcomplexity majorization-minimization (MM) algorithm is used to solve this problem. Numerical results show that the proposed scheme can achieve higher secrecy rate compared with the single IRS-aided scheme.

“…In [172], a practical transmission protocol was proposed to execute channel estimation and reflection optimization successively. In [173], a tailor-made three-phase pilot-based channel estimation framework was designed to estimate the overall uplink channels in an IRS system. However, the related energy costs for channel estimation and signaling overhead in these works are not taken into account, which somewhat conflicts with the purposes of applying IRSs.…”

Section: Open Research Problemsmentioning

confidence: 99%

Prospective Multiple Antenna Technologies for Beyond 5G

IEEE J. Select. Areas Commun.

Björnson

Matthaiou

et al. 2020

718

370

Multiple antenna technologies have attracted much research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are adopted. Since multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna technologies to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. Radically new approaches are required to achieve orders-of-magnitude improvements in these metrics. There will be large technical challenges, many of which are yet to be identified. In this paper, we survey three new multiple antenna technologies that can play key roles in beyond 5G networks: cellfree massive MIMO, beamspace massive MIMO, and intelligent reflecting surfaces. For each of these technologies, we present the fundamental motivation, key characteristics, recent technical progresses, and provide our perspectives for future research directions. The paper is not meant to be a survey/tutorial of a mature subject, but rather serve as a catalyst to encourage more research and experiments in these multiple antenna technologies. Index Terms-Beyond 5G, cell-free massive MIMO, beamspace, intelligent reflecting surface. I. INTRODUCTION T HE demand for higher data rates and traffic volumes seems to be never-ending, thus the quest for delivering The work of J.