Tabu-based adaptive large neighborhood search aids irregular reconfigurable intelligent surface capacity enhancement

The development of 6G has led to the need for communication systems to realize low latency, high throughput and stable connectivity. To achieve these goals, Reconfigurable Intelligent Surface has emerged. However, for RIS with massive elements, the overhead caused by channel estimation and feedback is not negligible. In this article, we address this problem using irregular RIS, which essentially involves irregularly rationing a specified number of reflective elements on an RIS surface, by providing additional spatial degrees of freedom to achieve performance gains. To this end, we formulate the problem of joint topology and precoding matrix joint optimization with tabu-based adaptive large neighborhood search for channel capacity maximization.