Simplified Optimization for Multi-Antenna MIMO Systems with Reduced Complexity

In this article, we present a novel approach to improve the performance of wireless communications using Reconfigurable Intelligent Surfaces (RISs). RISs are flat surfaces composed of many small reflecting elements that can manipulate the signal propagation in wireless networks. By carefully designing the reflection coefficients of these elements, we can significantly reduce the complexity of the system while maintaining its performance.
To achieve this goal, we formulate an optimization problem that minimizes the number of variables required to describe the RISs’ behavior. This problem is non-convex and requires a sophisticated solution method. We propose an iterative algorithm that converges to a practical and feasible solution by reducing the complexity of the system.
Our approach is validated through simulations, which show a significant enhancement in performance compared to traditional RIS-based communication systems. Moreover, we demonstrate that our proposed approach can be applied to multicast communications, where each receive antenna is activated and belongs to a specific user.
To make the solution more practical and feasible, we propose a suboptimal approach that avoids solving the optimization problem exactly. This allows us to find a good approximation of the optimal solution without requiring extensive computational resources.
In summary, our article presents a novel approach to enhance the performance of RIS-based wireless communications by reducing its complexity while maintaining its performance. Our proposed method is validated through simulations and can be applied to various communication scenarios, including multicast communications. By using a suboptimal approach, we make the solution more practical and feasible for real-world applications.