Joint optimization scheme for intelligent reflecting surface aided multi-relay networks

The latest research on hybrid networks of decode-and-forward (DF) relay and intelligent reflecting surface (IRS) is limited to just a single relay. To harvest multiple relay gains, this paper proposes a hybrid communication networks that combines multiple DF relays with an IRS. The authors formulate and address the joint optimization problem to maximize the end-to-end transmission rate by jointly optimizing the reflect beam forming, the best relay selection and the power allocation, subject to total transmit power constraint. Moreover, to better exploit the degrees of freedom, it is proposed that the source also transmits signals in the second time slot. While the optimization problem is difficult to solve, the authors propose some efficient approaches to make the problem tractable. First, power allocation problem is simplified by applying Cauchy-Schwarz inequality and introducing equivalent channel gain, second, non-convex rank-one constraint is overcome by utilizing semidefinite relaxation (SDR) approach, then the slacked non-convex constraint is overcome by applying first-order Taylor expansion approximation. The simulation results demonstrate that our proposed joint optimization scheme for hybrid networks of multiple DF relays with an IRS has significant performance improvement over the other optimization schemes, such as the optimization scheme for hybrid networks of single DF relay and an IRS.