一种人与人和机器到机器共存下能效最大化的上行用户分配算法

针对5G超密集异构蜂窝网络中人与人(H2H)和机器到机器(M2M)共存场景下有服务质量(QoS)保障和负载均衡的上行用户分配问题，该文提出一种基于匹配理论的用户分配算法。该算法在用户分配过程中同时考虑不同类型节点的接入控制策略，在最大化网络能效的同时，实现节点QoS保障。仿真结果表明，与其他算法相比，该算法不仅能够在能效、负载均衡以及QoS保障方面获得更好的性能，并且能获得与穷举法相近的性能。此外，所提算法的收敛速度很快且不受节点和基站数目变化的影响，适合解决H2H和M2M共存场景中的用户分配问题。

A User Association Algorithm for Maximizing Energy Efficiency with Human-to-Human and Machine-to-Machine Coexistence

In this paper, a match theory based uplink user association algorithm is proposed for maximizing energy efficiency and guaranteeing Quality of Service (QoS) requirements in a ultra-dense heterogeneous cellular networks with Human-to-Human (H2H) and Machine-to-Machine (M2M) coexistence. To maximize energy efficiency, balance load and guarantee QoS, simultaneously, the algorithm considers two access mechanisms for different types of node. Simulation results show that the proposed algorithm not only outperforms existing schemes in terms of the overall energy efficiency, the load balance and QoS guarantees, but also achieves the same performance as exhaustive search. Furthermore, the convergence speed of the algorithm is very fast, and is not affected by the number of base stations and nodes. Thus, the algorithm is suitable to solve the problem of user association, while considering the networks with H2H and M2M coexistence.