Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface With Discrete Phase Shifts

By Qingqing Wu, Rui Zhang. IEEE Transactions on Communications, 2019

1,206 citations recorded by the source corpus.

Intelligent reflecting surface (IRS) is a cost-effective solution for achieving high spectrum and energy efficiency in future wireless networks by leveraging massive low-cost passive elements that are able to reflect the signals with adjustable phase shifts. Prior works on IRS mainly consider continuous phase shifts at reflecting elements, which are practically difficult to implement due to the hardware limitation. In contrast, we study in this paper an IRS-aided wireless network, where an IRS with only a finite number of phase shifts at each element is deployed to assist in the communication from a multi-antenna access point (AP) to multiple single-antenna users. We aim to minimize the transmit power at the AP by jointly optimizing the continuous transmit precoding at the AP and the discrete reflect phase shifts at the IRS, subject to a given set of minimum signal-to-interference-plus-noise ratio (SINR) constraints at the user receivers. The considered problem is shown to be a mixed-integer non-linear program (MINLP) and thus is difficult to solve in general. To tackle this problem, we first study the single-user case with one user assisted by the IRS and propose both optimal and suboptimal algorithms for solving it. Besides, we analytically show that as compared to the ideal case with continuous phase shifts, the IRS with discrete phase shifts achieves the same squared power gain in terms of asymptotically large number of reflecting elements, while a constant proportional power loss is incurred that depends only on the number of phase-shift levels. The proposed designs for the single-user case are also extended to the general setup with multiple users among which some are aided by the IRS. Simulation results verify our performance analysis as well as the effectiveness of our proposed designs as compared to various benchmark schemes.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/b0fb124026ffe84100095d952a2ddf53e279dc85

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Citations in the corpus

Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, methodology): “The optimization solutions to the single-user MISO system in [156] can be extended to an MU case in [158].”
RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials (2021, background): “The power loss compared to a high-precision conﬁguration is only a few dB [18].”
Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming (2018, neutral): “The design of IRS with discrete phase shifts is addressed in our follow-up work [17].”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, methodology): “To tackle this new problem, instead of resorting to the commonly used semidefinite relaxation (SDR) method [5] or the successive refinement algorithm based on the block coordinate descent (BCD) method [6], we propose a new algorithm by leveraging the penalty dual decomposition (PDD) technique [27], ”
Modeling and Architecture Design of Reconfigurable Intelligent Surfaces Using Scattering Parameter Network Analysis (2020, background): “(cid:1) The optimization with discrete phase shifts has been well studied in [25], [26].”
Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimization (2019, background): “Next, we consider that the phase shift at each element of the IRS can only take a finite number of discrete values, which are equally spaced in [−π, π) [16].”
Joint Transmit Waveform and Passive Beamforming Design for RIS-Aided DFRC Systems (2021, background): “Motivated by the above, the applications of RIS in various wireless communication scenarios have been widely studied, including but not limited to the designs for maximizing spectral efficiency [10], [11], sum-rate [12]-[14], energy efficiency [15], [16], and minimizing transmit power [17], [18], et”
Active Reconfigurable Intelligent Surface-Aided Wireless Communications (2021, methodology): “Second, the variation of the load impedance is discreet with finite states due to the hardware limitations and the limited control link [34], [36].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, background): “In [183], the authors address the problem of beamforming optimization under practical discrete phase shift constraints at the RIS.”
Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications (2020, background): “have reported in [14]–[17], where a simple system model with only a single-antenna legitimate user and a single-antenna”
Capacity Characterization for Intelligent Reflecting Surface Aided MIMO Communication (2019, background): “3To characterize the capacity limit of IRS-aided MIMO systems, we assume that the phase-shift by each IRS element can be continuously adjusted, while the results of this paper can be readily extended to the practical setup with discrete phase-shift levels [19], [20].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [184], the authors address the problem of beamforming optimization under practical discrete phase shift constraints at the RIS.”
White Paper on Broadband Connectivity in 6G (2020, background): “The performance loss caused by using practical low-resolution hardware such as 1-bit IRS also needs to be carefully studied, especially for the case when a large number of reﬂecting elements is required to achieve a considerable beamforming gain [35].”
MIMO Transmission Through Reconfigurable Intelligent Surface: System Design, Analysis, and Implementation (2019, background): “2The impact of discrete phase shift has been taken into account in the literature [13], [32], [33], in which RIS works as a reflector for passive beamforming, rather than the RIS-based transmitter presented in this paper.”
Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security (2019, background): “the reflecting elements is costly in practice due to the hardware limitation, the SNR maximization problem and transmitter power minimization problem were studied in [20]–[23] by considering discrete reflecting coefficients on the reflecting elements.”