A Predictive Optimization Model for Path Loss Minimization for GSM Based Network Using Neuro-Swarm Intelligence
|International Journal of Computer Science and Engineering|
|© 2020 by SSRG - IJCSE Journal|
|Volume 7 Issue 2|
|Year of Publication : 2020|
|Authors : Igwe A. R, Anireh V.I.E, Nwaibu N.D|
How to Cite?
Igwe A. R, Anireh V.I.E, Nwaibu N.D, "A Predictive Optimization Model for Path Loss Minimization for GSM Based Network Using Neuro-Swarm Intelligence," SSRG International Journal of Computer Science and Engineering , vol. 7, no. 2, pp. 22-27, 2020. Crossref, https://doi.org/10.14445/23488387/IJCSE-V7I2P103
Path Loss is the reduction in power density of an electromagnetic wave as it travel, through space. It is a major component in the analysis and design of the telecommunication system. This study presents a predictive optimization model for minimizing path loss in GSM network using Neuro-Swarm Intelligence. Experiment performed include training data collected from GSM network provider using a feed forward propagation algorithm in a system with IPv4 network configuration. Simulation and determination of path loss (signal strength) based on distance, frequency and propagation speed of the data parameters whose termination criteria met the Mean Square Error (MSE). The program was coded in MATLAB. The result obtained was compared favourably with the best two (free space path loss and log normal shadowing model)
Path Loss, Minimization, GSM Network, Optimization, Prediction, Neuro-Swarm Intelligence
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