电力无线专网宏微协同组网中小区协作式故障检测

为了应对电力系统的数据流量增长、提升电力用户体验,电力无线专网系统将由密集部署的宏微小区组成,而网络中的故障小区会带来覆盖盲点从而影响网络服务质量.为了解决电力无线专网宏微协同组网中基于人工的故障检测方式效率低且成本高的问题,提出了一种基于迁移隐马尔可夫模型(transfer learning based hidden...

Cooperative cell outage detection in macro-micro collaborative networking in power wireless private networks

To adapt to the increase of data traffic in the power system and improve the experience of electrical users, the power wireless private networks envision a dense macro-micro collaborative networking, but the outage cells in networks can bring the blind areas to its coverage and influence its quality of service. To overcome the low efficiency and high cost of manual-based fault detection in macro-micro collaborative networking in power wireless private networks, a cooperative cell outage detection algorithm is designed in this paper through utilizing the transfer learning based hidden Markov model (TL-HMM). The proposed scheme aims to realize the automatic monitoring of cells and reduce the labor cost. The cells are first classified into four different states based on their anomaly levels. Then, the hidden Markov model is used to capture the current states of cells based on the relevant measurements reported by electrical users. Finally, to improve the convergence rate of HMM and reduce the number of training samples and required learning time, we propose a TLHMM-based cooperative cell outage detection algorithm. The simulation results demonstrate that the proposed TL-HMM based cooperative cell outage detection algorithm can not only speed up the learning process, but achieve an average detection accuracy of more than 90%.