Research on Power Optimization of Massive Machine Type of Communication Based on 5G Big Connection

In this paper, a resource allocation algorithm based on capacity maximization for massive Machine Type of Communication (mMTC) is studied. Taking LTE single cell as the background, considering the coexistence of LTE cellular user devices and mMTC devices, a two-layer network model is established in mMTC scenario, and mMTC gateway is introduced to analyze the transmit power control strategy of mMTC gateway (mMTCG) in mMTC scenario. On this basis, the bandwidth and power resource allocation problem in mMTC scenario is studied by using deep reinforcement learning algorithm to maximize the system capacity. The simulation results show that the proposed algorithm can improve the capacity of the system, and the power control is more consistent with the characteristics of mMTC scenario.