scholarly journals Planning Optimization of the Distributed Antenna System in High-Speed Railway Communication Network Based on Improved Cuckoo Search

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Zhaoyu Chen ◽  
Yanheng Liu ◽  
Geng Sun ◽  
Xu Zhou ◽  
Boyu Li ◽  
...  
Keyword(s):  
Communication Networks ◽  
High Speed ◽  
Search Algorithm ◽  
Network Planning ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Antenna System ◽  
High Speed Railway ◽  
Distributed Antenna System ◽  
Distributed Antenna

The network planning is a key factor that directly affects the performance of the wireless networks. Distributed antenna system (DAS) is an effective strategy for the network planning. This paper investigates the antenna deployment in a DAS for the high-speed railway communication networks and formulates an optimization problem which is NP-hard for achieving the optimal deployment of the antennas in the DAS. To solve this problem, a scheme based on an improved cuckoo search based on dimension cells (ICSDC) algorithm is proposed. ICSDC introduces the dimension cell mechanism to avoid the internal dimension interferences in order to improve the performance of the algorithm. Simulation results show that the proposed ICSDC-based scheme obtains a lower network cost compared with the uniform network planning method. Moreover, ICSDC algorithm has better performance in terms of the convergence rate and accuracy compared with the conventional cuckoo search algorithm, the particle swarm optimization, and the firefly algorithm.

WDM RoF-MMW and linearly located distributed antenna system for future high-speed railway communications

2015 ◽  
Vol 53 (10) ◽  
pp. 86-94 ◽  
Author(s):  
Pham Tien Dat ◽  
Atsushi Kanno ◽  
Naokatsu Yamamoto ◽  
Testuya Kawanishi
Keyword(s):  
High Speed ◽  
Antenna System ◽  
High Speed Railway ◽  
Distributed Antenna System ◽  
Distributed Antenna

Fault diagnosis of railway freight car wheelset based on deep belief network and cuckoo search algorithm

2021 ◽  
pp. 095440972110291
Author(s):  
Honghui Li ◽  
Hongkun Wang ◽  
Ziwen Xie ◽  
Mengqi He
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Deep Belief Network ◽  
Belief Network ◽  
Railway Freight ◽  
Hybrid Simulated Annealing ◽  
Technical Issues

As the key running part of the railway freight transportation system, the wheel not only bears the load of the vehicle, but also ensures the running and steering of the car body on the rails. The frequent high-speed friction with the rail and brake is the main reason for early failure of wheelset tread. Therefore, real-time status monitoring and early fault diagnosis of wheel treads have become key technical issues that must be solved in the reform of the railway freight maintenance system. In this paper, an adaptive hybrid Simulated Annealing Cuckoo Search algorithm (SA-ACS) is proposed and applied to the Deep Belief Network (DBN). The SA-ACS-DBN algorithm is used to improve the training speed and convergence accuracy of the diagnosis model. Finally, it is found through the comparison experiment of wheel tread fault data that the data results prove the feasibility of the SA-ACS-DBN model in the application of wheelset fault diagnosis.

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