Author(s)

Stephen Ojo^1*, Taiwo P. Ojo², Victor Ojong Etta³

¹College of Engineering, Anderson University, Anderson, USA.
²Department of Management Information Systems, Girne American University, Girne, Northern Cyprus.
³Computer Science Department, Florida A & M University, Tallahassee, USA.

Empirical and deterministic models have not proven to be effective in path loss predictions because of the problems of computational complexities, low accuracies, and inability to generalize. To solve these problems relating to path loss predictions, this article presents an optimal path loss propagation model developed at 3.4 GHz with the use of fuzzy logic. We introduced Fuzzy logic to accurately represent all forms of uncertainties in the data spectrum as the signal propagates from the transceiver to the receiver, thereby producing accurate results. Experimental data were collected across Cyprus at 3.4 GHz and compared with three existing path loss models. The fuzzy-logic path loss prediction model was then developed and compared with the experimental data and with each of the theoretical empirical models, the newly developed model predicted signal loss with the greatest accuracy as it gives the lowest root-mean-square error. The newly developed model is very efficient for signal propagation and path loss prediction.

Signal Loss, Fuzzy-Logic, Machine Learning, Signal Propagation, Accuracy, Empirical, Deterministic

Ojo, S. , Ojo, T. and Etta, V. (2022) A Fuzzy-Logic Based Path Loss Model at 3.4 GHz for LTE Networks. Open Journal of Applied Sciences, 12, 1271-1283. doi: 10.4236/ojapps.2022.127087.