基于5G无人机通信的多智能体异构网络选择方法

5G无人机通信网络和各种不同无线接入技术的结合使无线异构网络呈现多样化的发展趋势。然而,用户繁多且不同的业务请求对网络要求也不同,造成网络接入选择问题。提出了一种基于5G无人机通信的多智能体异构网络选择方法,将用户分为多个智能体,从用户端和网络端两个方面出发,将用户侧的时延和传输速率需求与网络侧的负载均衡需求综合考虑作为即时回报的相关参数,通过基于Nash Q-Learning的算法进行学习,得到异构网络环境下的网络选择决策模型。仿真结果表明,所提异构网络选择方法针对不同业务类型用户的需求均能选择合适的网络,同时均衡网络的负载,充分利用异构无线网络的资源。

Multi-agent heterogeneous network selection method based on 5G UAV communication

The combination of 5G UAV communication and different wireless access technologies makes wireless heterogeneous networks present a diversified development trend.However, various types of service requests by users have different requirements on the heterogeneous networks, which leads to the problem of network selection.A multi-agent heterogeneous network selection method based on 5G UAV communication was proposed.Specifically, the users were divided into multiple agents.From the two aspects of the user side and the network side, the delay and transmission rate requirements of the user side and the load balancing requirement of the network side were comprehensively considered as the relevant parameters of immediate reward.The simulation results show that the proposed heterogeneous network selection method can select the appropriate network according to the needs of users of different service types, balance the load of the network, and make full use of the resources of the heterogeneous wireless network.