Abstract

Reconfigurable intelligent surfaces (RISs) have emerged as promising contenders for enabling sixth-generation (6G) physical wireless platforms. RISs fine-tune wireless networks to optimize the spectrum and energy use. This article explores the design challenge of a joint beamforming strategy for increasing throughput at the AP and RIS sides. To address this challenging problem, we created an iterative algorithm, that makes use of the Duality Theory and the Alternating Optimization technique called the DAO algorithm. Due to the given problem's non-convexity and difficulty with variable coupling, the proposed Algorithm divides the optimization problem of the coupled variables into four distinct optimization sub-problems by introducing new supporting variables. The alternate optimization strategy handles the issue sequentially by iteratively updating these new variables, the active beamformer, and the non-active beamformer. Finally, the simulation results indicate that we achieve about a 30% spectrum boost over the standard network without RIS for a certain system and circumstances scenario.

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