Performance analysis of ultra-dense heterogeneous network switching technology based on region awareness Bayesian decision - Xie, Chaochen; Zhao, Jianzhou; Guo, Rujing; Li, Li; Lu, Chao (Soft computing (Berlin, Germany), 2020)
The network switching is one of the most important techniques, which keeps continuous communication between two users. A variety of approaches and strategies (such as fuzzy logic control, neural network, smart algorithm etc.) have been proposed to confront this problem. These approaches and strategies play an important role in reducing delays, decreasing drop call rates, and improving QoS during switching. However, the existing techniques and strategies often apply to some special scenarios, such as between WLAN and WiFi (or WiMAX, or 3G, or UTMS and LTE). Facing the ultra-dense heterogeneous network in the 5G communication system, this brings great difficulties to the switching, especially how to properly select a service network. Whether the existing methods and strategies are feasible remains to be studied. For solving the switching in a complication networks environment, a novel switching way is proposed in this paper. We adopt the technology of regional awareness and combine with Bayes’ decision strategy to explore the switching of ultra-dense heterogeneous network. This way effectively solves the difficult problem of selecting a service network in the convention. Finally, we analyze the err probability of the proposed way. The experimental results show that our scheme can properly select the switched network in the 5G system, and the probability of the handover error is the lowest, which ensures the rationality and effectiveness of the network handover. Therefore, the proposed way in this paper is feasible.