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- W2134716768 abstract "Constraint programming is the study of system which is based on constraints. The solution of a constraint satisfaction problem is a set of variable value assignments, which satisfies all members of the set of constraints in the CSP. In this paper the application of constraint satisfaction programming is to be used in predicting the path loss of various indoor propagation models using Depth First Search Algorithm, which is basic algorithm of CSP. After predicting the path loss at different set of parameters such as frequencies , floor attenuation factor , path loss exponent , we find the optimum set of parameter frequency , floor attenuation factor , path loss exponent at which the path loss is minimum. For this optimization CSP provides an optimization algorithm called Branch and Bound Algorithm. Presents the additional path loss caused by the floors between transmitter and receiver by considering the average floor attenuation factors found for up to floors of the building. A comparative analysis has been done to validate the applicability of these three different indoor propagation models at various frequencies and distances." @default.
- W2134716768 created "2016-06-24" @default.
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- W2134716768 date "2013-02-28" @default.
- W2134716768 modified "2023-09-28" @default.
- W2134716768 title "Predicting the Suitable Parameters of Indoor Propagation Model Using CSP Algorithm" @default.
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