面向复杂环境的超密集网络小区合并技术研究OA

Although the deployment of ultra-dense networks can effectively address the data rate challenges posed by the rapid growth of wireless Internet of Things(IoT)devices in future networks,it also introduces severe inter-cell interference.To tackle this issue,a mathematical model of the cell merging problem is constructed.A performance evaluation metric based on a linear combination of spectral efficiency(SE)and energy efficiency(EE)is proposed to measure the optimization level of the system,with the objective of maximizing overall communication capacity.To solve the resulting integer programming problem,an experience-based cell merging algorithm and a tabu search-based cell merging algorithm are proposed.Extensive simulations are conducted to compare the impact of different merging strategies on system communication performance.Simulation results show that the application of cell merging techniques can significantly improve the signal-to-interference-plus-noise ratio(SINR).Moreover,the proposed algorithms effectively overcome the limitations of experience-based strategies in optimizing SE and EE,achieving an additional improvement in system communication capacity on top of an approximate 7 dB increase in SINR.