Research on IRS-assisted communication optimization method based on federated learning

In recent years, intelligent reflective surfaces (IRS) have been widely used to improve communication quality. IRS has the characteristics of low cost and no delay, and can be densely deployed to meet the communication needs of a large number of devices. In this paper, IRS is applied to the downlink multi-user communication system, and a central optimization algorithm is proposed for rate optimization design. At the same time, with the increasing demand of users for privacy, this paper designs a federated learning (FL) optimization algorithm to establish a rate optimization model for multi-user systems under the premise of ensuring data security.