Abstract
Deploying reconfigurable intelligent surface (RIS) to enhance wireless transmission is a promising approach. In this paper, we investigate large-scale multi-RIS-assisted multi-cell systems, where multiple RISs are deployed in each cell. Different from the full-buffer scenario, the mutual interference in our system is not known a priori, and for this reason we apply the load coupling model to analyze this system. The objective is to minimize the total resource consumption subject to user demand requirement by optimizing the reflection coefficients in the cells. The cells are highly coupled and the overall problem is non-convex. To tackle this, we first investigate the single-cell case with given interference, and propose a low-complexity algorithm based on the Majorization-Minimization method to obtain a locally optimal solution. Then, we embed this algorithm into an algorithmic framework for the overall multi-cell problem, and prove its feasibility and convergence to a solution that is at least locally optimal. Simulation results demonstrate the benefit of RIS in time-frequency resource utilization in the multi-cell system.
Highlights
A N array of new technologies that can contribute to beyond 5G (B5G) and the sixth-generation (6G) wireless networks are being proposed and extensively investigated, including massive multiple-input multiple-output (m-MIMO) [1] or utilizing higher frequency bands such as millimeter wave [2] and even terahertz (THz) [3]
We propose an algorithm based on the MajorizationMinimization (MM) method to obtain a locally optimal solution
With fi (ρ−i, φ−i, Ψi) and Lemma 6, we propose an algorithmic framework based on the following iteration to obtain a locally optimal solution
Summary
A N array of new technologies that can contribute to beyond 5G (B5G) and the sixth-generation (6G) wireless networks are being proposed and extensively investigated, including massive multiple-input multiple-output (m-MIMO) [1] or utilizing higher frequency bands such as millimeter wave (mmWave) [2] and even terahertz (THz) [3]. To apply these technologies, it may be necessary to develop new network software and hardware platforms. As deploying RIS in a wireless network is modular, it is more suitable for upgrading current wireless systems
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