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.　©　2024　IEEE.