Simulation analysis methods for mobile communication network traffic characteristics evaluations

2002 ◽  
Vol 86 (4) ◽  
pp. 86-93 ◽  
Author(s):  
Masaki Okamoto ◽  
Yutaka Yoshida
Keyword(s):  
Communication Network ◽  
Mobile Communication ◽  
Network Traffic ◽  
Simulation Analysis ◽  
Mobile Communication Network ◽  
Traffic Characteristics ◽  
Analysis Methods

scholarly journals Power Level Distributions of Radio Base Station Equipment and User Devices in a 3G Mobile Communication Network in India and the Impact on Assessments of Realistic RF EMF Exposure

IEEE Access ◽  
2015 ◽  
Vol 3 ◽  
pp. 1051-1059 ◽  
Author(s):  
Paramananda Joshi ◽  
Mukesh Agrawal ◽  
Bjorn Thors ◽  
Davide Colombi ◽  
Ashwani Kumar ◽  
...  
Keyword(s):  
Communication Network ◽  
Mobile Communication ◽  
Power Level ◽  
Base Station ◽  
Mobile Communication Network ◽  
The Impact

scholarly journals Research on Distributed 5G Signal Coverage Detection Algorithm Based on PSO-BP-Kriging

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4390
Author(s):  
Tingli Xiang ◽  
Hongjun Wang
Keyword(s):  
Neural Network ◽  
Communication Network ◽  
Mobile Communication ◽  
Detection Algorithm ◽  
Base Station ◽  
Distributed Sensor ◽  
Mobile Communication Network ◽  
The Neural Network ◽  
Signal Coverage ◽  
5G Mobile Communication

In order to overcome the limitations of traditional road test methods in 5G mobile communication network signal coverage detection, a signal coverage detection algorithm based on distributed sensor network for 5G mobile communication network is proposed. First, the received signal strength of the communication base station is collected and pre-processed by randomly deploying distributed sensor nodes. Then, the neural network objective function is modified by using the variogram function, and the initial weight coefficient of the neural network is optimized by using the improved particle swarm optimization algorithm. Next, the trained network model is used to interpolate the perceptual blind zone. Finally, the sensor node sampling data and the interpolation estimation result are combined to generate an effective coverage of the 5G mobile communication network signal. Simulation results indicate that the proposed algorithm can detect the real situation of 5G mobile communication network signal coverage better than other algorithms, and has certain feasibility and application prospects.

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