scholarly journals Mobile Communication Network Optimization System Based on Artificial Intelligence

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Chao Duan ◽  
Jun Luo
Keyword(s):  
Artificial Intelligence ◽  
Communication Network ◽  
Communication Networks ◽  
Mobile Communication ◽  
Network Optimization ◽  
Specific Content ◽  
Optimization System ◽  
Mobile Communication Network ◽  
Artificial Intelligence Technology ◽  
Intelligent Technology

The objective of this paper is to study the key technology of the mobile communication network optimization system based on artificial intelligence technology. Specific Content. This paper designs the artificial intelligence agent- (IA-) type mobile communication network optimization tool iOS2CMCN, analyzes the relevant intelligent technology introduced into the system, and analyzes the feasibility and practicability of iOS2CMCN through application examples. The results show that the optimization of mobile communication networks is one of the important links in the construction of communication networks and ensuring the quality of network service. In the form of an artificial intelligence agent, iOS2CMCN absorbs the experience and knowledge of a large number of network optimization engineers and experts and realizes the intelligence and automation of mobile communication network optimization. It is proven that the fuzzy technology is introduced in theory, the practical problem is reasonably modeled, and the rule and case reasoning are used to simulate the thinking mode of a human being when solving the problem. It reduces the dependence of network optimization on humans, improves the efficiency of network optimization, and provides a new idea for practical mobile communication network optimization.

AN ISING MODEL SIMULATION OF MOBILE COMMUNICATION NETWORKS

2006 ◽  
Vol 17 (03) ◽  
pp. 435-445 ◽  
Author(s):  
L. F. CARAM ◽  
C. F. CAIAFA ◽  
A. N. PROTO
Keyword(s):  
Communication Network ◽  
Ising Model ◽  
Communication Networks ◽  
Mobile Communication ◽  
Model Simulation ◽  
Dynamical Behavior ◽  
Critical Parameters ◽  
Mobile Communication Network ◽  
Commercial Operation ◽  
Virtual Temperature

We studied the dynamical behavior of a mobile communication network through a traditional Ising model. In the mobile communication network, each cell has N channels to process the calls, and they arrive with a given rate, having different lengths. In our Ising model we introduce cooperation among cells. This mechanism is considered in the normal commercial operation today. Through our simulation we evaluate the (virtual) temperature, magnetization, and the critical parameters of the network. The description of a mobile communication network, using a well-known theoretical model, is an important tool to improve the performance of these networks.

scholarly journals Optimization of Signal Coverage Area in Mobile Communication Networks

2020 ◽  
pp. 35-45
Author(s):  
O. A. Osahenvemwen
Keyword(s):  
Mathematical Model ◽  
Communication Network ◽  
Communication Networks ◽  
Mobile Communication ◽  
Load Capacity ◽  
Base Station ◽  
Coverage Area ◽  
Mobile Communication Network ◽  
Signal Coverage ◽  
Mobile Communication Networks

This study presents the optimization of signal coverage area in third generation WCDMA technology of mobile communication networks, aim at improving signal coverage area or overcoming the presence dead zone in mobile communication network. Various parameters that affect Signal coverage area in mobile communication network were determined. Optimization mathematical model based on Lagrange mathematical method was developed in line with the necessary parameters and characteristics. The developed mathematical model was simulated using MATLAB and Wolfram Mathematical Software using data obtain from mobile communication Network ‘A’ at Asaba, Delta State. The obtained data were number of duplex channels, frequency, load capacity of the base station, interference, distance power received, power transmitted etc. The result obtain are the critical points with fade-off of the radio signal. The coverage area indicates a non-linear function, therefore to minimize threshold parameter such as interference; pathloss and power received values will increase as the coverage area of the base station increases.

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