A Learning-based Radio Resource Control Mechanism for Variousand Dynamic Wireless Communication Environments

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This study discusses a mechanism that enables individual wireless nodes to `act' appropriately according to their various and dynamic communication environments. The `actions' here include decision making for frequency channel selection, transmission poweradjustment, and transmission format selection. This study modeled the problem as a `bargaining' problem between wireless nodes. Then, the communication control algorithm and the communication protocol were designed based on the Nash bargaining solution, which was introduced from the game theory. The simulation results showed the proposed algorithm and protocol work well.