Dynamic Reconfiguration Using Signal Processing for Artificial Intelligence

Abstract

A newly developed meta-surface reconfigurable intelligent surface has been singled out as a top choice for 6G mobile communications networks. By reflecting signals, RIS might effectively install new communication conduits. Meanwhile, it has been widely accepted in recent years that AI may be a useful tool. With the help of artificial intelligence (AI), RIS communications will be more capable of adapting to new situations and more resilient to interference. Artificial intelligence (AI) may tackle contemporary signal processing problems in a data-driven manner by extracting the inherent features from the real data, in addition to the conventional model-driven methodologies. Because of this, AI is well-suited for the digital signal problems through RIS networks under less-than-ideal settings such as modeling mismatch, a shortage of resources, hardware deterioration, and dynamic transmissions. As one of the first survey articles on the topic, we will discuss the application of AI and RIS, or artificial intelligence and radio frequency identification systems, to a wide range of signal processing tasks, including environmental sensing, channel acquisition, directional antenna design, bandwidth allocation, etc. In addition, we'll discuss the challenges of AIRIS and provide some promising future directions.