Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network

Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network

Blog Article

In order to satisfy the diversified communication requirements of terminal source nodes in power distribution network, it is necessary to optimize Blazer the communication orchestration in power distribution unified communication network.Firstly, we construct the joint optimization problem of data transmission delay and energy consumption.Then, the joint optimization problem is modeled as a multi-armed bandit problem, and an adversarial reinforcement learning-based communication orchestration algorithm for power distribution unified communication network is proposed, which uses Waist Bags the historical orchestration information and the perceived adversary between source nodes to dynamically learn the communication orchestration strategy.Finally, the superior performance of the proposed algorithm is verified through simulation.