Artificial Intelligence Approach to Signal Propagation Modeling for Outdoor to Indoor Wireless Communication Networks: A Proposed Study

Abstract

The growing interest in wireless indoor wireless communication systems and applications of local area networks has resulted in many investigations on the characteristics of indoor radio propagation channels. In the last few years, several empirical channel models have been developed based on indoor channel measurements. The design and deployment of Wi-Fi, 3G and 4G wireless networks employing new technologies has become all the more crucial, and requires careful site-specific planning and prediction of all appropriate mobile channel parameters. There is huge demand in the wireless industry for the development of accurate propagation prediction techniques. In this field, the current trend in indoor prediction is shifting from empirical models to complex deterministic models, due to their decreasing computation cost and the increasing requirement for wideband prediction, which is by empirical models reduced. This study is intended to develop a local outdoor to indoor propagation model using artificial fuzzy neural networks, which aims to be really suitable for outdoor to indoor propagation prediction. Also for almost all of the path loss models, being used at the moment by all the Kenyan mobile operators, have not been developed using Kenyan structures. So there is need for developing a model that can be more accurate with Kenyan buildings since our buildings are quite different for instance out there in Europe or first world countries there are no slums as is the case with Kenya and other African countries. The model will be developed by first obtaining continuous wave (CW) measurements for given categories of buildings, analyzing them and using artificial fuzzy neural networks in the process of coming up with the model. After the model is developed it will be compared with current models.