IRS-Assisted Green Communication Systems: Provable Convergence and Robust Optimization

Yu X, Xu D, Ng DWK, Schober R (2021)

Publication Type: Journal article

Publication year: 2021

Journal

IEEE Transactions on Communications Institute of Electrical and Electronics Engineers (IEEE)

DOI: 10.1109/TCOMM.2021.3087794

Abstract

In this paper, we investigate resource allocation for IRS-assisted green multiuser multiple-input single-output (MISO) systems. To minimize the total transmit power, both the beamforming vectors at the access point (AP) and the phase shifts at multiple IRSs are jointly optimized, while taking into account the minimum required quality-of-service (QoS) of multiple users. First, two novel algorithms, namely a penalty-based alternating minimization (AltMin) algorithm and an inner approximation (IA) algorithm, are developed to tackle the non-convexity of the formulated optimization problem when perfect channel state information (CSI) is available. Existing designs employ semidefinite relaxation in AltMin-based algorithms, which, however, cannot ensure convergence. In contrast, the proposed penalty-based AltMin and IA algorithms are guaranteed to converge to a stationary point and a Karush-Kuhn-Tucker (KKT) solution of the design problem, respectively. Second, the impact of imperfect knowledge of the CSI of the channels between the AP and the users is investigated. To this end, a non-convex robust optimization problem is formulated and the penalty-based AltMin algorithm is extended to obtain a stationary solution. Simulation results reveal a key trade-off between the speed of convergence and the achievable total transmit power for the two proposed algorithms. In addition, we show that the proposed algorithms can significantly reduce the total transmit power at the AP compared to various baseline schemes and that the optimal numbers of transmit antennas and IRS reflecting elements, which maximize the system energy efficiency of the considered system, are finite.

Authors with CRIS profile

Dongfang Xu Lehrstuhl für Digitale Übertragung (IDC) Robert Schober Lehrstuhl für Digitale Übertragung (IDC)

Involved external institutions

Hong Kong University of Science and Technology (HKUST) / 香港科技大學 CN China (CN) University of New South Wales (UNSW) AU Australia (AU)

How to cite

APA:

Yu, X., Xu, D., Ng, D.W.K., & Schober, R. (2021). IRS-Assisted Green Communication Systems: Provable Convergence and Robust Optimization. IEEE Transactions on Communications. https://doi.org/10.1109/TCOMM.2021.3087794

MLA:

Yu, Xianghao, et al. "IRS-Assisted Green Communication Systems: Provable Convergence and Robust Optimization." IEEE Transactions on Communications (2021).

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