Investigation on Indoor Distributed System Planning Modeling and Fast Algorithm for 5G Mobile Communication Network

Description

In the 5G era, most new services such as smart homes, smart factories, and virtual reality will occur in indoor scenarios. Therefore, indoor coverage systems will become the top priority of 5G network construction. This project establishes a room distribution systemplanning model with the goal of low cost, high coverage, and low power consumption. The variable-length coding strategy is adopted to realize the synchronization optimization of the network structure and parameters, and the fast solving algorithm is designed basedon the individual generation mechanism of deep reinforcement learning and the strategy of adaptively allocating computing resources. The research of this project can significantly improve the service quality of the 5G indoor network and the efficiency of indoor distribution system planning and has important scientific significance and social and economic benefits.