Abstract:
Recent technological development has facilitated the deployment of different Mobile Broadband Cellular Network
Systems (MBCNS), such as Long Term Evolution (LTE) and 5G New Radio (NR), globally. This development aims at satisfying the
ever-data-hungry multimedia applications to guarantee good quality of service for mobile subscribers. One way mobile subscribers
can continuously access and enjoy the services provided by the MBCNS is to put in place a well-planned signal coverage area,
wherein accurate path loss estimation is prioritized. Particularly, with the regular technological advancements and evolution of
mobile communication systems, particularly fourth and fifth, the development of accurate précised path loss models has
become more critical for robust planning and optimization purposes. In practice, the conventional log-distance path loss model is
suitable for path loss predictive modeling and estimation in plain signal propagation environments. However, the model is not
suitable for irregular terrains. In order to adapt this model for application in irregular terrains, this paper proposes a modified log distance path loss model with an adaptive polynomial term. The modified long-distance path loss model provides efficient irregular
terrain signal loss estimation parameters. In order to boost the prediction accuracy of the proposed model, two regression
optimization methods, non-linear least square and weighted least square, were employed with the Levenberg-Marquardt (LM)
algorithm to determine its relevant parameters. In terms of the coefficient of correlation and percentage error, the modified log distance path loss model with the optimized parameters showed 40-60% improvement in accuracy over the standard log-distance
model for the path loss prediction across the six different locations investigated. Furthermore, the validation of the proposed model
has been provided in order to ascertain the level of its prediction accuracies in other locations. Overall, the modified log-distance
model showed remarkable accuracy and efficiency when deployed in a related wireless propagation environment.
