IRS-Enabled Interference Elimination and Fairness Enhancement in D2D Communication Networks

In order to cope with the increasing data traffic, we try to enable Intelligent Reflecting Surface (IRS) interference elimination in Device-to-Device (D2D) communication networks to improve the Signal Interference Noise Ratio (SINR). We build the system model and divide the original problem into two subproblems: IRS reflection parameter adjustment and IRS allocation. We use the the Cross Entropy Global Optimization Method (CEGOM) to solve the first subproblem. For the second subproblem, in order to ensure the fairness of user rates and avoid user starvation, we propose a heuristic algorithm based on the Max-Min Fairness Method (MMFM) to solve the problem. Simulation results demonstrate the superiority of the proposed algorithms, which improves Jain's fairness index by 70%, 72% and 13% and reduces the blocking probability by 92%, 90% and 82%, respectively, when compared to the random, shortest distance, and traditional MMFM strategies.