长期演进网络中基于粒子群的天线下倾角自优化方法

Antenna down-tilt angle self-optimization method based on particle swarm in long term evolution network

针对第三代合作伙伴项目(3GPP)中自组织网络(SON)的覆盖与容量自优化问题,提出了一种基于粒子群优化(PSO)算法的有源天线下倾角优化方法。首先,确定基站(eNB)中传输数据的用户设备(UE)数,用户测量上报邻小区参考信号接收功率(RSRP)信息和位置信息;然后,确定优化目标预设适应度评价函数为频谱效率(SE);其次,将下倾角同时优化问题看作是多维优化问题,选择天线下倾角为粒子集合,使用PSO算法求解得到天线下倾角的最优值;最后,通过系统自主调整优化下倾角,实现长期演进(LTE)网络中容量及覆盖的自优化。通过建模及仿真结果分析,此算法在优化目标不同时可以取得不同的优化效果:优化目标为用户平均频谱效率时,采用传统黄金分割优化算法频谱效率较初始设定提升12.9%,采用PSO算法可提升22.5%;调整优化目标为用户加权平均频谱效率时,对边缘用户,传统黄金分割优化算法并无明显提升,PSO算法取得了19.3%的优化提升。实验结果表明,该方法可提升用户吞吐量,改善系统性能。

To solve the coverage and capacity optimization problem of Self-Organizing Network （SON） in the 3rd Generation Partnership Project （3GPP）, an active antenna down-tih angle optimization method based on Particle Swarm Optimization （PSO） algorithm was proposed. First, the number of User Equipments （UE） served by evolved Node B （eNB） was determined, and the Reference Signal Received Power （RSRP） and position measured from the UE were obtained. Second, the Spectral Efficiency （SE） was regarded as the fitness function which defined by optimization goals. Then, down-tilt angle optimization was regarded as multidimensional optimization problem, and antenna down-tilt angle was regarded as the set of particles to resolve the optimal value by the PSO algorithm. Finally, the capacity and coverage self-optimization of Long Term Evolution （LTE） networks was achieved by adjusting down-tih angle independently. By simulations, different objective functions made different optimization results. When the average spectrum efficiency was set as the optimization goal, the spectral efficiency of traditional golden section algorithm increased by 12.9% than primary settings, the spectral efficiency of PSO was increased by 22.5%. When the weighted average spectral efficiency was set as the optimization goal, the spectral efficiency of golden section algorithm was not significantly improved but that of PSO was increased by 19.3% for edge users. The experimental results show that the proposed method improves cell throughput and system performance.