Computation of 10 Knife Edge Diffraction Loss Using Epstein-Peterson Method

Wali Samuel

doi:10.11648/j.ajsea.20170601.11

Abstract

In this paper, application of Epstein-Peterson method in the computation of a ten (10) multiple knife edge diffraction loss is presented for a 1 GHz microwave link. In the computation, each of the ten obstructions gave rise to a virtual hop which resulted in a knife edge diffraction loss. What is peculiar to the Epstein-Peterson method is how the virtual hops are identified or defined. The overall diffraction loss, according to the Epstein-Peterson method is the sum of the diffraction loss computed for each of the ten virtual hops. In the results, the highest LOS clearance height of 5.727273 m occurred in virtual hop 5 whereas the highest diffraction parameter of 0.333333 and the highest virtual hop diffraction loss of 8.908754dB occurred in virtual hop1. The lowest LOS clearance height of 0.4 m, the lowest diffraction parameter 0.029814 and the lowest virtual hop diffraction loss, 6.290874 dB occurred in virtual hop 9. In all, the overall effective diffraction loss for the 10 knife edge obstructions as computed by the Epstein-Peterson is 69.93384 dB.

Highlights

In multiple knife edge diffraction loss calculation, two or more knife egde obstructions are considered where the height of each of the obstructions extends above the line of site (LOS) [1,2,3,4,5]
In the Epstein-Peterson multiple knife edge diffraction loss method, for any given hop j, the clearance height to its LOS is given as h where; h = h !"# = H − H
Each of the ten obstructions gave rise to a virtual hop which resulted in a knife edge diffraction loss

Summary

American Journal of Software Engineering and Applications

2017; 6(1): 1-4 http://www.sciencepublishinggroup.com/j/ajsea doi: 10.11648/j.ajsea.20170601.11 ISSN: 2327-2473 (Print); ISSN: 2327-249X (Online) To cite this article: Wali Samuel, Trust Christopher Oguichen, Steve Worgu. Computation of 10 Knife Edge Diffraction Loss Using Epstein-Peterson Method. American Journal of Software Engineering and Applications. Vol 6, No 1, 2017, pp. 1-4. doi: 10.11648/j.ajsea.20170601.11 Received: January 3, 2017; Accepted: January 10, 2017; Published: February 3, 2017

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