Optimized Wireless Channel Power Resource Allocation Based on Graph Attention Network
In order to better optimize the transmission power of nodes in ad hoc networks and further improve the overall network throughput,this paper proposes a transmission power allocation algorithm based on graph neural network(GNN)theory.This algorithm takes the"unfolded weighted minimum mean square error"(UWMMSE)iterative algorithm as the overall framework,introduces the"graph attention network"model in the iterative structure,and trains specific parameters through unsupervised learning mechanism,while maintaining good optimization performance and accelerating algorithm convergence.The simulation results show that the power optimization allocation algorithm proposed in the paper can significantly reduce computational complexity while achieving better performance than similar algorithms.
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