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Wireless Propagation Models Optimization using Artificial Neural Network Algorithm | IEEE Conference Publication | IEEE Xplore

Wireless Propagation Models Optimization using Artificial Neural Network Algorithm


Abstract:

A metaheuristic approach to optimize measured path loss values using the Artificial Neural network Algorithm is presented in this paper. This paper consists of the standa...Show More

Abstract:

A metaheuristic approach to optimize measured path loss values using the Artificial Neural network Algorithm is presented in this paper. This paper consists of the standard Hata model equations, COST 231 model equations, and Ericsson model equations for establishing the values of path loss in an urban city medium via computation. The optimization technique used in this paper is based on graphically computing the best possible path for a signal to propagate and will experience minimum environmental effects in order to retain most of the information carried and minimize the loss. Hence, the optimized values of the measured path loss are obtained. For improved charting and applicability of mobile cellular networks, a few existing techniques require optimization to provide improved quality of service and efficient floor planning over a crowded geographical area for placing antennas, under a particular service band.
Date of Conference: 21-22 January 2022
Date Added to IEEE Xplore: 10 March 2022
ISBN Information:
Conference Location: Goa, India

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