Path Loss Correction for Signal Propagation amongst Low Roof Top Buildings using Fuzzy Logic

Abstract

Performance of current path attenuation prediction models encounters huge deviation from their true behavior when deployed for the locality apart from the one for which it had been proven for. This work deals with introducing the path loss on the basis of measured data and representation of the same in a different approach for the mentioned Fuzzy Inference system based analysis. The empirical data collection followed by curve-fitting for path loss evaluation on decibel scale with Normal random variable distribution for representing the shadow fading. Our paper introduces a new methodology for prediction of path loss for betterment in QoS via. Network planning specifically for mobility prone communication systems deploying fuzzy approach. The Transmission discontinuities encountered during propagation has been differentiated in to a variety of factors defined as fuzzy sets such as free space, flat terrain, low foliage terrain, high foliage terrain, and country side terrain. path loss exponent (n) has been applied for varied propagation profiles, Mamdani Fuzzy Inference has been deployed for prediction of "n" path loss exponent for any kind of scenario, which was obtained on the basis of set of symbolic rules that avails an approximation to the known propagation scenarios. Bertoni's model proposed by H.L. Bertoni's has been used for the present analysis.

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

“…The model is proven to have better performance by accurately predicting path loss. In [94], a model for predicting path loss based on the fuzzy method is proposed. This model uses free space, vegetation terrain, flat terrain, and rural terrain to establish a fuzzy set.…”

“…For instance, Sotiroudis et al proposed a path loss propagation model based on ANN for urban scenes and used the Differential Evolution (DE) algorithm to lay out an optimal ANN for path loss prediction [21]. In [94], a model is proposed based on a fuzzy method and curve-fitting for a suburban scene. Fuzzy sets are used to distinguish between the transmission discontinuities encountered during propagation.…”