Optimizing the Path Loss of Wireless Indoor Propagation Models Using CSP Algorithms

Abstract

Constraint programming is the study of computational system based on constraints. The idea of constraint programming is to solve problem by stating constraints about the problem and consequently finding the solution satisfying all the constraints. In this paper the application of constraint satisfaction programming is used in predicting the path loss of various indoor propagation models using chronological backtrack algorithm, which is basic algorithm of CSP. After predicting the path loss at different set of parameters such as frequencies(f), floor attenuation factor(faf), path loss cofficient(n), penetration attenuation factor(paf), we find the optimum set of parameter (frequency (f), floor attenuation factor(faf), path loss cofficient(n), penetration attenuation factor(paf) at which path loss is minimum. The Branch and bound algorithm is used to optimized the constraint satisfaction problem. The comparison of the models are analysed with and without CSPs.