@article{MAKHILLJEAS201813715965,
    title = {Base Line Knowledge on Propagation Modelling and Prediction
Techniques in Wireless Communication Networks},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {7},
    pages = {1919-1934},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.1919.1934},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.1919.1934},
    author = {Virginia,Joseph and},
    keywords = {propagation modelling,Radio signals,propagation models,adaptive propagation prediction,neural networks,channels},
    abstract = {One fundamental contributing factor to planning a workable and efficient wireless radio
communication networks as well as improving existing ones lies on the ability to precisely predict the strength
and coverage of radio signals between the transmitters and receivers in the system networks. The mathematical
algorithms and tools used for these predictions are popularly referred to as propagation models. This research
presents a detailed baseline surveyed of different types of propagation models and prediction techniques in
cellular communication networks. Some of the key propagation models discussed include the Hata, SUI,
Walfiscsh-Ikegami, Walficsh-Bertoni, Lee and ITU Models. The peculiar characteristics and limitations of the
existing models has been shown. The research is completed by proposing an adaptive propagation prediction
modelling algorithms which caters for stochastic signal attenuation phenomenon and the inhomogeneity of the
spatial propagation channels.}
    }