Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks

By Huayan Guo, Ying-Chang Liang, Jie Chen, Erik G. Larsson. IEEE Transactions on Wireless Communications, 2019

900 citations recorded by the source corpus.

Reconfigurable intelligent surfaces (RIS) is a promising solution to build a programmable wireless environment via steering the incident signal in fully customizable ways with reconfigurable passive elements. In this paper, we consider a RIS-aided multiuser multiple-input single-output (MISO) downlink communication system. Our objective is to maximize the weighted sum-rate (WSR) of all users by joint designing the beamforming at the access point (AP) and the phase vector of the RIS elements, while both the perfect channel state information (CSI) setup and the imperfect CSI setup are investigated. For perfect CSI setup, a low-complexity algorithm is proposed to obtain the stationary solution for the joint design problem by utilizing the fractional programming technique. Then, we resort to the stochastic successive convex approximation technique and extend the proposed algorithm to the scenario wherein the CSI is imperfect. The validity of the proposed methods is confirmed by numerical results. In particular, the proposed algorithm performs quite well when the channel uncertainty is smaller than 10%.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/dfbd7dad10de80af0a5d0282eebb2068fec9e188

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Citations in the corpus

Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design (2020, background): “…at the users in [15], maximize the minimum user rate subject to a transmit power constraint in the asymptotic regime in [16], minimize the transmit power at the BS subject to users’ individual SINR constraints in [14] and maximize the sum-rate subject to a transmit power constraint in [17], [18].”
Active RIS vs. Passive RIS: Which Will Prevail in 6G? (2021, methodology): “To account for small-scale fading, following [40], we adopt the Ricean fading channel model for all channels involved.”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, neutral): “d) Manifold approach [107]–[111]: There exist different”
Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications (2019, background): “The precoding problem for multi-user MIMO is proven to be non-convex and NP-hard [9], hence researchers tried to find the near-optimal joint-beamforming solutions for RIS-aided communications [10], [11].”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, methodology): “As shown, the PDD-based algorithm achieves a similar performance as the algorithm in [11].”
A Joint Precoding Framework for Wideband Reconfigurable Intelligent Surface-Aided Cell-Free Network (2020, result): “This simplified subproblem P̂passive is similar to those in [19], [38].”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, methodology): “Considering a similar IRS-assisted MU MISO system, the authors in [136] extend the sum-rate maximization problem with perfect CSI to the case with imperfect CSI.”