Naslov
Indoor Field Strength Prediction Based on Neural Network Model and Particle Swarm Optimization

Autori
Vilović, Ivan ; Burum, Nikša ; Šipuš, Zvonimir

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
23rd International Review of Progress in Applied Computational Electromagnetics / Barmada, Sami - Verona : Applied Computational Electromagnetic Society ACES, 2007, 1082-1089

Skup
23rd International Review of Progress in Applied Computational Electromagnetics

Mjesto i datum
Verona, Italija, 19.03.2007. - 23.03.2007

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Indoor propagation; Neural network; Optimization; Particle swarm

Sažetak
This paper deals with an indoor propagation problem where it is difficult to rigorously obtain the field strength distribution. We have developed a propagation model based on a neural network, which has advantages of deterministic (high accuracy) and empirical (short computation time) approaches. The neural network architecture, based on the multilayer perception, is used to absorb the knowledge about the given environment through training based on measurements. Such network then becomes capable to predict signal strength that includes absorption and reflection effects without additional computation and measurement efforts. The neural network model is used as a cost function in the optimization of the base station location. As optimization algorithm we have applied the particle swarm optimization (PSO) algorithm, i.e. a global optimization routine based on the movement of particles and their intelligence. Appropriate PSO parameters are discussed in the paper, and the results of PSO are compared with results obtained with two standard algorithms such as simplex optimization method and Powell's conjugate direction method.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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