Muti-Layer Fuzzy Logic Sets for Mobile Path Loss in Forests

Abstract

Mobile path loss prediction in forests using Multi-Layer fuzzy logic system (MLFS) is presented in this paper. The MLFS consists of a tree density decision layer which is a supervisory layer in order to select the next layers using fuzzy decision. The sub-predictions use a set of rule base that provide path loss prediction in each case of an environment. These crisp inputs are classified by the fuzzifier to fuzzy sets and then inferenced using fuzzy linguistic rule base into multi -output path loss slopes via de-fuzzifier. For this study, we classified the terrains into high-, medium-, low-density and grass area and used the simple linguistic rules for prediction of the path loss slopes. We performed measurements in different forest densities at a frequency of 1.8 GHz with base station antenna height in a range of 3, 4, and 5 m above ground while the receiving antenna height was fixed at 1.8 m above ground. The results have shown that fuzzy logic approach provides more accurate prediction of path loss slopes than that of conventional empirical mathematic models. The proposed models will be useful for the local wireless network and micro-cell design of mobile communication systems in forests.

Adaptive differential amplitude pulse‐position modulation technique for optical wireless communication channels based on fuzzy logic

“…Fuzzy logic is a practical mathematical addition to classic Boolean logic. The areas of application of fuzzy logic have spread from consumer electronics to industrial control, information processing, financial analysis, robotics, communication and network and much more in just the past few years [15][16][17][18][19][20][21][22][23][24].…”