A Low-Complexity Algorithmic Framework for Large-Scale IRS-Assisted Wireless Systems

Ma Y, Shen Y, Yu X, Zhang J, Song SH, Letaief KB (2020)


Publication Type: Conference contribution

Publication year: 2020

Publisher: Institute of Electrical and Electronics Engineers Inc.

Conference Proceedings Title: 2020 IEEE Globecom Workshops, GC Wkshps 2020 - Proceedings

ISBN: 9781728173078

DOI: 10.1109/GCWkshps50303.2020.9367432

Abstract

Intelligent reflecting surfaces (IRSs) are revolutionary enablers for next-generation wireless communication networks, with the ability to customize the radio propagation environment. To fully exploit the potential of IRS-assisted wireless systems, reflective elements have to be jointly optimized with conventional communication techniques. However, the resulting optimization problems pose significant algorithmic challenges, mainly due to the large-scale non-convex constraints induced by the passive hardware implementations. In this paper, we propose a low-complexity algorithmic framework incorporating alternating optimization and gradient-based methods for largescale IRS-assisted wireless systems. The proposed algorithm provably converges to a stationary point of the optimization problem. Extensive simulation results demonstrate that the proposed framework provides significant speedups compared with existing algorithms, while achieving a comparable or better performance.

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How to cite

APA:

Ma, Y., Shen, Y., Yu, X., Zhang, J., Song, S.H., & Letaief, K.B. (2020). A Low-Complexity Algorithmic Framework for Large-Scale IRS-Assisted Wireless Systems. In 2020 IEEE Globecom Workshops, GC Wkshps 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc..

MLA:

Ma, Yifan, et al. "A Low-Complexity Algorithmic Framework for Large-Scale IRS-Assisted Wireless Systems." Proceedings of the 2020 IEEE Globecom Workshops, GC Wkshps 2020 Institute of Electrical and Electronics Engineers Inc., 2020.

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