A 3D Parabolic Equation (PE) Based Technique for Predicting Propagation Path Loss in an Urban Area

Abstract

A mobile radio environment places fundamental limitations on the performance of wireless communication systems. Most models developed to predict propagation path loss have been historically performed in a statistical approach. These models are expensive to develop and do not offer the accuracy, computational advantages, and sufficiency as the parabolic equation (PE). The goal of this thesis is to develop a 3D model based on PE for predicting propagation path loss in urban areas on flat and hilly terrain. The PE method offers the computational advantages, where one can approximate the elliptic operator governing the true wave behavior by a much simpler parabolic operator that permits marching in range. Moreover those all-important aspects of propagation such as reflection and diffraction are included automatically in the formulation. Four test problems on flat terrain and two test problems on hilly terrain will be simulated. For the flat terrain, the 3D PE model results will be compared with the two-ray, the four-ray, the UTD, and the numerical integration technique results. For the hilly terrain, the results of the 3D PE model will be compared with the UTD and the numerical integration technique results.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2001
Accession Number
ADA397355

Entities

People

  • Keem B. Thiem

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Algorithms
  • California
  • Communication Systems
  • Diffraction
  • Electromagnetic Wave Propagation
  • Equations
  • Frequency Domain
  • Fresnel Integrals
  • Geometry
  • Magnetic Fields
  • Mobile Communications
  • Numerical Integration
  • Urban Areas
  • Wave Propagation
  • Wireless Communications

Readers

  • Computational Modeling and Simulation
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Wave Propagation and Nonlinear Chaotic Dynamics.