Introduction to Rf Propagation

Total Page:16

File Type:pdf, Size:1020Kb

Introduction to Rf Propagation INTRODUCTION TO RF PROPAGATION John S. Seybold, Ph.D. JOHN WILEY & SONS, INC. INTRODUCTION TO RF PROPAGATION INTRODUCTION TO RF PROPAGATION John S. Seybold, Ph.D. JOHN WILEY & SONS, INC. Copyright © 2005 by John Wiley & Sons, Inc. All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com. Library of Congress Cataloging-in-Publication Data: Seybold, John S., 1958– Introduction to RF propagation / by John S. Seybold. p. cm. Includes bibliographical references and index. ISBN-13 978-0-471-65596-1 (cloth) ISBN-10 0-471-65596-1 (cloth) 1. Radio wave propagation—Textbooks. 2. Radio wave propagation—Mathematical models—Textbooks. 3. Antennas (Electronics)—Textbooks. I. Title. QC676.7.T7S49 2005 621.384¢11—dc22 2005041617 Printed in the United States of America 10987654321 To: My mother, Joan Philippe Molitor and my father, Lawrence Don Seybold CONTENTS Preface xiii 1. Introduction 1 1.1 Frequency Designations 1 1.2 Modes of Propagation 3 1.2.1 Line-of-Sight Propagation and the Radio Horizon 3 1.2.2 Non-LOS Propagation 5 1.2.2.1 Indirect or Obstructed Propagation 6 1.2.2.2 Tropospheric Propagation 6 1.2.2.3 Ionospheric Propagation 6 1.2.3 Propagation Effects as a Function of Frequency 9 1.3 Why Model Propagation? 10 1.4 Model Selection and Application 11 1.4.1 Model Sources 11 1.5 Summary 12 References 12 Exercises 13 2. Electromagnetics and RF Propagation 14 2.1 Introduction 14 2.2 The Electric Field 14 2.2.1 Permittivity 15 2.2.2 Conductivity 17 2.3 The Magnetic Field 18 2.4 Electromagnetic Waves 20 2.4.1 Electromagnetic Waves in a Perfect Dielectric 22 2.4.2 Electromagnetic Waves in a Lossy Dielectric or Conductor 22 2.4.3 Electromagnetic Waves in a Conductor 22 2.5 Wave Polarization 24 2.6 Propagation of Electromagnetic Waves at Material Boundaries 25 2.6.1 Dielectric to Dielectric Boundary 26 vii viii CONTENTS 2.6.2 Dielectric-to-Perfect Conductor Boundaries 31 2.6.3 Dielectric-to-Lossy Dielectric Boundary 31 2.7 Propagation Impairment 32 2.8 Ground Effects on Circular Polarization 33 2.9 Summary 35 References 36 Exercises 36 3. Antenna Fundamentals 38 3.1 Introduction 38 3.2 Antenna Parameters 38 3.2.1 Gain 39 3.2.2 Effective Area 39 3.2.3 Radiation Pattern 42 3.2.4 Polarization 44 3.2.5 Impedance and VSWR 44 3.3 Antenna Radiation Regions 45 3.4 Some Common Antennas 48 3.4.1 The Dipole 48 3.4.2 Beam Antennas 50 3.4.3 Horn Antennas 52 3.4.4 Reflector Antennas 52 3.4.5 Phased Arrays 54 3.4.6 Other Antennas 54 3.5 Antenna Polarization 55 3.5.1 Cross-Polarization Discrimination 57 3.5.2 Polarization Loss Factor 58 3.6 Antenna Pointing loss 62 3.7 Summary 63 References 64 Exercises 65 4. Communication Systems and the Link Budget 66 4.1 Introduction 66 4.2 Path Loss 67 4.3 Noise 69 4.4 Interference 76 4.5 Detailed Link Budget 79 4.5.1 EIRP 80 4.5.2 Path Loss 80 4.5.3 Receiver Gain 82 4.5.4 Link Margin 83 4.5.5 Signal-to-Noise Ratio 83 CONTENTS ix 4.6 Summary 84 References 85 Exercises 85 5. Radar Systems 87 5.1 Introduction 87 5.2 The Radar Range Equation 88 5.3 Radar Measurements 93 5.3.1 Range Measurement 93 5.3.2 Doppler Measurement 95 5.3.3 Angle Measurement 95 5.3.4 Signature Measurement 98 5.4 Clutter 99 5.4.1 Area Clutter 99 5.4.2 Volume Clutter 105 5.4.3 Clutter Statistics 106 5.5 Atmospheric Impairments 106 5.6 Summary 107 References 108 Exercises 109 6. Atmospheric Effects 111 6.1 Introduction 111 6.2 Atmospheric Refraction 112 6.2.1 The Radio Horizon 112 6.2.2 Equivalent Earth Radius 113 6.2.3 Ducting 116 6.2.4 Atmospheric Multipath 117 6.3 Atmospheric Attenuation 121 6.4 Loss From Moisture and Precipitation 125 6.4.1 Fog and Clouds 126 6.4.2 Snow and Dust 130 6.5 Summary 131 References 132 Exercises 132 7. Near-Earth Propagation Models 134 7.1 Introduction 134 7.2 Foliage Models 134 7.2.1 Weissberger’s Model 135 7.2.2 Early ITU Vegetation Model 135 7.2.3 Updated ITU Vegetation Model 137 x CONTENTS 7.2.3.1 Terrestrial Path with One Terminal in Woodland 138 7.2.3.2 Single Vegetative Obstruction 138 7.3 Terrain Modeling 141 7.3.1 Egli Model 141 7.3.2 Longley–Rice Model 143 7.3.3 ITU Model 144 7.4 Propagation in Built-Up Areas 146 7.4.1 Young Model 146 7.4.2 Okumura Model 146 7.4.3 Hata Model 151 7.4.4 COST 231 Model 152 7.4.5 Lee Model 153 7.4.6 Comparison of Propagation Models for Built-Up Areas 157 7.5 Summary 159 References 160 Exercises 161 8. Fading and Multipath Characterization 163 8.1 Introduction 163 8.2 Ground-Bounce Multipath 164 8.2.1 Surface Roughness 174 8.2.2 Fresnel Zones 175 8.2.3 Diffraction and Huygen’s Principle 179 8.2.4 Quantifying Diffraction Loss 179 8.3 Large-Scale or Log-Normal Fading 186 8.4 Small-Scale Fading 193 8.4.1 Delay Spread 194 8.4.2 Doppler Spread 198 8.4.3 Channel Modeling 199 8.4.4 The Probabilistic Nature of Small-Scale Fading 200 8.5 Summary 203 References 205 Exercises 206 9. Indoor Propagation Modeling 208 9.1 Introduction 208 9.2 Interference 208 9.3 The Indoor Environment 209 9.3.1 Indoor Propagation Effects 209 9.3.2 Indoor Propagation Modeling 210 CONTENTS xi 9.3.3 The ITU Indoor Path Loss Model 210 9.3.4 The Log-Distance Path Loss Model 214 9.4 Summary 216 References 216 Exercises 216 10. Rain Attenuation of Microwave and Millimeter Wave Signals 218 10.1 Introduction 218 10.2 Link Budget 219 10.3 Rain Fades 222 10.3.1 Specific Attenuation Due to Rainfall 222 10.3.2 The ITU Model 224 10.3.3 The Crane Global Model 229 10.3.4 Other Rain Models 234 10.3.5 Rain Attenuation Model Comparison 234 10.3.6 Slant Paths 234 10.4 The Link Distance Chart 234 10.5 Availability Curves 237 10.6 Other Precipitation 237 10.7 Cross-Polarization Effects 239 10.8 Summary 239 References 240 Exercises 241 Appendix 10A: Data for Rain Attenuation Models 242 11. Satellite Communications 246 11.1 Introduction 246 11.2 Satellite Orbits 247 11.3 Satellite Operating Frequency 249 11.4 Satellite Path Free-Space Loss 249 11.5 Atmospheric Attenuation 252 11.6 Ionospheric Effects 255 11.7 Rain Fades 255 11.7.1 ITU Rain Attenuation Model for Satellite Paths 257 11.7.2 Crane Rain Attenuation Model for Satellite Paths 264 11.7.3 The DAH Rain Attenuation Model 270 11.8 Antenna Considerations 273 11.9 Noise Temperature 274 11.9.1 The Hot-Pad Formula 276 11.9.2 Noise Due to Rain 278 11.9.3 Sun Outages 279 11.10 Summary 279 xii CONTENTS References 280 Exercises 281 12. RF Safety 283 12.1 Introduction 283 12.2 Biological Effects of RF Exposure 285 12.3 CC Guidelines 287 12.4 Antenna Considerations 290 12.5 FCC Computations 292 12.5.1 Main Beam and Omnidirectional Antenna Analysis 292 12.5.2 Antenna Directivity 293 12.6 Station Evaluations 297 12.7 Summary 298 References 298 Exercises 299 Appendix A: Review of Probability for Propagation Modeling 301 Index 317 PREFACE With the rapid expansion of wireless consumer products, there has been a con- siderable increase in the need for radio-frequency (RF) planning, link plan- ning, and propagation modeling.
Recommended publications
  • Comparative Analysis of Path Loss Prediction Models for Urban Macrocellular Environments
    COMPARATIVE ANALYSIS OF PATH LOSS PREDICTION MODELS FOR URBAN MACROCELLULAR ENVIRONMENTS A. Obota, O. Simeonb, J. Afolayanc Department of Electrical/Electronics & Computer Engineering, University of Uyo, Akwa Ibom State, Nigeria. aEmail: [email protected] bEmail: [email protected] cEmail: [email protected] Abstract A comparative analysis of path loss prediction models for urban macrocellular environments is presented in this paper. Specifically, three path loss prediction models namely free space, Hata and Egli were used to predict path losses. The calculated path loss values were compared with practical measured data obtained from a Visafone base station located in Uyo, Nigeria. The comparative analysis reveals that the mean square error (MSE) for free space, Hata and Egli were 16.24dB, 2.37dB and 8.40dB respectively. The results showed that Hata's model is the most accurate and reliable path loss prediction model for macrocellular urban propagation environments, since its MSE value of 2.37dB is smaller than the acceptable minimum MSE value of 6dB for good signal propagation. Keywords: macrocellular areas, path loss prediction models, Hata model, mean square error 1. Introduction nals generally propagate by means of any or a combination of these three basic propaga- Nowadays, wireless communication technol- tion mechanisms; reflection, diffraction, and ogy is influencing every area of modern life, scattering [2, 3]. One of the most impor- and has encouraged useful researches in nearly tant features of the propagation environment all fields of human endeavour. Cellular ser- is path (propagation) loss. Path loss is de- vices are today being used by millions of peo- fined as the difference (in dB) between the ple worldwide.
    [Show full text]
  • On Adaptive Neuro-Fuzzy Model for Path Loss Prediction in the Vhf Band
    ITU Journal: ICT Discoveries, Special Issue No. 1, 2 Feb. 2018 ON ADAPTIVE NEURO-FUZZY MODEL FOR PATH LOSS PREDICTION IN THE VHF BAND Nazmat T. Surajudeen-Bakinde1, Nasir Faruk2, Muhammed Salman1, Segun Popoola3, Abdulkarim Oloyede2, Lukman A. Olawoyin2 1Department of Electrical and Electronics Engineering, University of Ilorin, Nigeria 2Department of Telecommunication Science, University of Ilorin, Ilorin, Nigeria 3Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria Email: [email protected]; [email protected]; faruk.n, deenmat, oloyede.aa, olawoyin.la{@unilorin.edu.ng} Abstract – Path loss prediction models are essential in the planning of wireless systems, particularly in built-up environments. However, the efficacies of the empirical models depend on the local ambient characteristics of the propagation environments. This paper introduces artificial intelligence in path loss prediction in the VHF band by proposing an adaptive neuro-fuzzy (NF) model. The model uses five-layer optimized NF network based on back propagation gradient descent algorithm and least square errors estimate. Electromagnetic field strengths from the transmitter of the NTA Ilorin, which operates at a frequency of 203.25 MHz, were measured along four routes. The prediction results of the proposed model were compared to those obtained via the widely used empirical models. The performances of the models were evaluated using the Root Mean Square Error (RMSE), Spread Corrected RMSE (SC-RMSE), Mean Error (ME), and Standard Deviation Error (SDE), relative to the measured data. Across all the routes covered in this study, the proposed NF model produced the lowest RMSE and ME, while the SDE and the SC-RMSE were dependent on the terrain and clutter covers of the routes.
    [Show full text]
  • Development of a Radiowave Propagation Model for Hilly Areas
    International Journal of Electronics Communication and Computer Engineering Volume 4, Issue 2, ISSN (Online): 2249–071X, ISSN (Print): 2278–4209 Development of a Radiowave Propagation Model for Hilly Areas Famoriji J. Oluwole, Olasoji Y. Olajide Abstract – Achieving optimal performance is a paramount III. THE COST-231 HATA MODEL FOR URBAN concern in wireless networks. One of the strategies is to use wireless empirical models to predict wireless link quality ENVIRONMENT factors such as path loss and the received power in any given transmission domain with irregular terrain. Measurement The COST-231 Hata wireless propagation model was results of signal strength in UHF band obtained in Idanre devised as an extension to the Hata-Okumura model and Town of Ondo State Nigeria were validated against the Hata model as reported by Abhayawardhana et al.,[3]. theoretical estimations. Okumura-Hata model, COST231- The COST-231Hata model is designed to be used in the Hata model and Egli model applicable for path loss frequency band from 500 MHz to 2000 MHz. It also prediction in area with high hill were examined. These models predictions were compared with predictions from contains corrections for urban, suburban and rural (flat) measurements taken in Idanre to determine the path loss environments. [3] also noted that ”although this models’ prediction error for each model. Consequently, modified frequency range is outside that of the measurements, its COST231-Hata model was developed for path loss prediction simplicity and the availability of correction factors has in the hilly areas. The model developed has 6.02% error seen it widely used for path loss prediction at this which made it applicable for hilly areas (Idanre).
    [Show full text]
  • Comparative Analysis of Basic Models and Artificial Neural Network
    Progress In Electromagnetics Research M, Vol. 61, 133–146, 2017 Comparative Analysis of Basic Models and Artificial Neural Network Based Model for Path Loss Prediction Julia O. Eichie1, *,OnyediD.Oyedum1, Moses O. Ajewole2, and Abiodun M. Aibinu3 Abstract—Propagation path loss models are useful for the prediction of received signal strength at a given distance from the transmitter; estimation of radio coverage areas of Base Transceiver Stations (BTS); frequency assignments; interference analysis; handover optimisation; and power level adjustments. Due to the differences in: environmental structures; local terrain profiles; and weather conditions, path loss prediction model for a given environment using any of the existing basic empirical models such as the Okumura-Hata’s model has been shown to differ from the optimal empirical model appropriate for such an environment. In this paper, propagation parameters, such as distance between transmitting and receiving antennas, transmitting power and terrain elevation, using sea level as reference point, were used as inputs to Artificial Neural Network (ANN) for the development of an ANN based path loss model. Data were acquired in a drive test through selected rural and suburban routes in Minna and environs as dataset required for training ANN model. Multilayer perceptron (MLP) network parameters were varied during the performance evaluation process, and the weight and bias values of the best performed MLP network were extracted for the development of the ANN based path loss models for two different routes, namely rural and suburban routes. The performance of the developed ANN based path loss model was compared with some of the existing techniques and modified techniques.
    [Show full text]
  • Broadcasting Transmitters in Kampala Metropolitan; Uganda
    Asian Journal of Research and Reviews in Physics 3(4): 65-78, 2020; Article no.AJR2P.63843 ISSN: 2582-5992 Modeling the Distribution of Radiofrequency Intensities from the Digital Terrestrial Television (DTTV) Broadcasting Transmitters in Kampala Metropolitan; Uganda Peter Opio1*, Akisophel Kisolo1, Tumps W. Ireeta1 and Willy Okullo1 1Department of Physics, College of Natural Science, Makerere University, P.O.Box 7062, Kampala, Uganda. Authors’ contributions This work was carried out in collaboration among all authors. Author PO designed the study, performed the statistical analysis, wrote the protocol, managed the literature searches and wrote the first draft of the manuscript. Authors AK, TWI and WO managed the analyses of the study. All authors read and approved the final manuscript Article Information DOI: 10.9734/AJR2P/2020/v3i430130 Editor(s): (1) Prof. Shi-Hai Dong, Instituto Politécnico Nacional, Mexico. Reviewers: (1) Sigit Haryadi, Institut Teknologi Bandung, Indonesia. (2) Wahyu Pamungkas, Institut Teknologi Telkom Purwokerto, Indonesia. Complete Peer review History: http://www.sdiarticle4.com/review-history/63843 Received 06 October 2020 Original Research Article Accepted 11 December 2020 Published 26 December 2020 ABSTRACT This study presents the modeling of the distribution of RF intensities from the Digital Terrestrial Television (DTTV) broadcasting transmitter in Kampala metropolitan. To achieve this, the performance evaluation of the different path loss propagation models and envisaging the one most suitable for Kampala metropolitan was done by comparing the path loss model values with the measured field Reference Signal Received Power (RSRP) values. The RSRP of the DTTV broadcasting transmitter were measured at operating frequencies of 526 MHz, 638 MHz, 730 MHz and 766 MHz using the Aaronia Spectran HF-6065 V4 spectrum analyzer, Aaronia AG HyperLOG 4025 Antenna at 1.5 m and 2.5 m heights, Aaronia GPS Logger, real time Aaronia MCS spectrum-analysis-software and a T430s Lenovo Laptop.
    [Show full text]
  • Introduction to Rf Propagation
    INTRODUCTION TO RF PROPAGATION John S. Seybold, Ph.D. ,WILEY- 'iNTERSCIENCE JOHN WILEY & SONS, INC. CONTENTS Preface XIII 1. Introduction 1.1 Frequency Designations 1 1.2 Modes of Propagation 3 1.2.1 Line-of-Sight Propagation and the Radio Horizon 3 1.2.2 Non-LOS Propagation 5 1.2.2.1 Indirect or Obstructed Propagation 6 1.2.2.2 Tropospheric Propagation 6 1.2.2.3 Ionospheric Propagation 6 1.2.3 Propagation Effects as a Function of Frequency 9 1.3 Why Model Propagation? 10 1.4 Model Selection and Application 11 1.4.1 Model Sources H 1.5 Summary 12 References 12 Exercises 13 2. Electromagnetics and RF Propagation 14 2.1 Introduction 14 2.2 The Electric Field 14 2.2.1 Permittivity 15 2.2.2 Conductivity 17 2.3 The Magnetic Field 18 2.4 Electromagnetic Waves 20 2.4.1 Electromagnetic Waves in a Perfect Dielectric 22 2.4.2 Electromagnetic Waves in a Lossy Dielectric or Conductor 22 2.4.3 Electromagnetic Waves in a Conductor 22 2.5 Wave Polarization 24 2.6 Propagation of Electromagnetic Waves at Material Boundaries 25 2.6.1 Dielectric to Dielectric Boundary 26 vii VÜi CONTENTS 2.6.2 Dielectric-to-Perfect Conductor Boundaries 31 2.6.3 Dielectric-to-Lossy Dielectric Boundary 31 2.7 Propagation Impairment 32 2.8 Ground Effects on Circular Polarization 33 2.9 Summary 35 References 36 Exercises 36 3. Antenna Fundamentals 38 3.1 Introduction 38 3.2 Antenna Parameters 38 3.2.1 Gain 39 3.2.2 Effective Area 39 3.2.3 Radiation Pattern 42 3.2.4 Polarization 44 3.2.5 Impedance and VSWR 44 3.3 Antenna Radiation Regions 45 3.4 Some Common Antennas 48 3.4.1 The Dipole 48 3.4.2 Beam Antennas 50 3.4.3 Hörn Antennas 52 3.4.4 Reflector Antennas 52 3.4.5 Phased Arrays 54 3.4.6 Other Antennas 54 3.5 Antenna Polarization 55 3.5.1 Cross-Polarization Discrimination 57 3.5.2 Polarization Loss Factor 58 3.6 Antenna Pointing loss 62 3.7 Summary "3 References "4 Exercises "5 4.
    [Show full text]
  • An Assessment of Path Loss Tools and Practical Testing of Television White Space Frequencies for Rural Broadband Deployments
    University of New Hampshire University of New Hampshire Scholars' Repository Master's Theses and Capstones Student Scholarship Fall 2015 An Assessment of Path Loss Tools and Practical Testing of Television White Space Frequencies for Rural Broadband Deployments Braden Scott Blanchette University of New Hampshire, Durham Follow this and additional works at: https://scholars.unh.edu/thesis Recommended Citation Blanchette, Braden Scott, "An Assessment of Path Loss Tools and Practical Testing of Television White Space Frequencies for Rural Broadband Deployments" (2015). Master's Theses and Capstones. 1048. https://scholars.unh.edu/thesis/1048 This Thesis is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Master's Theses and Capstones by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. AN ASSESSMENT OF PATH LOSS TOOLS AND PRACTICAL TESTING OF TELEVISION WHITE SPACE FREQUENCIES FOR RURAL BROADBAND DEPLOYMENTS BY BRADEN SCOTT BLANCHETTE Bachelor of Science in Electrical Engineering, The University of New Hampshire, 2013 THESIS Submitted to the University of New Hampshire in Partial Fulfillment of the Requirements for the Degree of Master of Science in Electrical Engineering September, 2015 ii This thesis has been examined and approved in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering by: Thesis Director, Dr. Nicholas Kirsch, Assistant Professor of Electrical and Computer Engineering Dr. Michael Carter, Associate Professor of Electrical and Computer Engineering Dr. Richard Messner, Associate Professor of Electrical and Computer Engineering On August 10, 2015 Original approval signatures are on file with the University of New Hampshire Graduate School.
    [Show full text]
  • Radio Propagation Modeling on 433 Mhz
    Radio propagation modeling on 433 MHz Ákos Milánkovich1, Károly Lendvai1, Sándor Imre1, Sándor Szabó1 1 Budapest University of Technology and Economics, Műegyetem rkp. 3-9. 1111 Budapest, Hungary {milankovich, lendvai, szabos, imre}@hit.bme.hu Abstract. In wireless network design and positioning it is essential to use radio propagation models for the applied frequency and environment. There are many propagation models available for both indoor and outdoor environments; however, they are not applicable for 433 MHz ISM frequency, which is perfectly suitable for smart metering and sensor networking applications. During our work, we gathered the most common propagation models available in scientific literature, broke them down to components and analyzed their behavior. Based on our research and measurements, a method was developed to create a propagation model for both indoor and outdoor environment optimized for 433 MHz frequency. The possible application areas of the proposed models: smart metering, sensor networks, positioning. Keywords: Radio propagation model, 433 MHz, smart metering, positioning 1 Introduction We are accustomed to use various wirelessly communicating devices, which possess different transmission properties according to their application areas. There are devices operating at high bandwidth in short range, but can not percolate walls. On the contrary, other devices can penetrate all kinds of materials for long distances, but operate on lower bandwidth. The transmission properties of these various technologies – beyond transmission power and antenna characteristics – are principally determined by the operating frequency range of the system. In addition, the operating frequency determines the amount of attenuation for the technology, caused by different media. The ability of calculating the signal strength in a given distance from the transmitter is severely important in case of network planning, because such a model helps us to determine where to place the devices, so that the system operates properly.
    [Show full text]
  • Radio Coverage Prediction for a Wireless IP-Based Network in Central Europe
    Radio Coverage Prediction for a Wireless IP-based Network in Central Europe Ralf Wilke DH3WR, Hubertus A. Munz and Dirk Heberling Institute of High Frequency Technology RWTH Aachen University Aachen, Germany [email protected] Abstract—In the beginning of 2009 the idea of building up a point-to-point radio links are displayed on a map. An excerpt wireless IP-based data network emerged from Austria. The of this map is shown in Fig. 1. classical backbone approach with distributed locations of routers, servers and user access equipment was pursued. Today in 2014, the network is covering Central Europe and still spreading. Every week new backbone interconnections and user access points are being installed. Based on an open source framework, a wiki-like website serves as an administrative platform, where IP assignments, meta-data and geographical locations of backbone nodes are stored. This paper presents the selection and implementation of RF propagation models to automatically predict the radio coverage area of user access points and display them on a map. As the RF path lengths differ from 300 m up to 30 km, several models where reviewed and merged into one software. The prediction was done based on a digital elevation model and land cover data. Keywords—RF prediction, wireless user access, coverage, HamNet I. INTRODUCTION In the 2009 the Austrian amateur radio community started to build up a wireless network. The frequencies used are in the 2.4 GHz and 5.7 GHz WiFi band. Due to the fact that the operators are licensed radio amateurs, the EIRP of those installations is not limited to the regulations which apply for Fig.
    [Show full text]
  • Optimised COST-231 Hata Models for Wimax Path Loss Prediction in Suburban and Open Urban Environments
    www.ccsenet.org/mas Modern Applied Science Vol. 4, No. 9; September 2010 Optimised COST-231 Hata Models for WiMAX Path Loss Prediction in Suburban and Open Urban Environments Mardeni.R Faculty of Engineering, Multimedia University Jalan Multimedia, 63100 Cyberjaya, Malaysia Tel: 60-3-8312-5481 E-mail: [email protected] T. Siva Priya (Corresponding author) Faculty of Engineering, Multimedia University Jalan Multimedia, 63100 Cyberjaya, Malaysia Tel: 60-12-287-6023 E-mail: [email protected] Abstract In Malaysia, the incumbent WiMAX operator utilises the bands of 2360-2390MHz to provide broadband services. Like all Radio Frequency (RF), WiMAX is susceptible to path loss. In this paper, field strength data collected in Cyberjaya, Malaysia is used to calculate the path loss suffered by the WiMAX signals. The measured path loss is compared with the theoretical path loss values estimated by the COST-231 Hata model, the Stanford University Interim (SUI) model and the Egli model. The best model to estimate the path loss based on the path loss exponents was determined to be the COST-231 Hata model. From this observation, an optimised model based on COST-231 Hata parameters is developed to predict path loss for suburban and open urban environments in the 2360-2390MHz band. The optimised model is validated using standard deviation error analysis, and the results indicate that the new optimised model predicts path loss in both suburban and open urban environments with very low standard deviation errors of less than 4.3dB and 1.9dB respectively. These values show that the model optimisation was done successfully and that the new optimised models will be able to determine the path loss suffered by the WiMAX signals more accurately.
    [Show full text]
  • Adjustment of Lee Path Loss Model for Suburban Area in Kuala Lumpur-Malaysia
    2011 International Conference on Telecommunication Technology and Applications Proc .of CSIT vol.5 (2011) © (2011) IACSIT Press, Singapore Adjustment of Lee Path Loss Model for Suburban Area in Kuala Lumpur-Malaysia Jalel Chebil+, Ali K. Lwas, Md. Rafiqul Islam and Al-Hareth Zyoud Department of Electrical and Computer Engineering Faculty of Engineering, International Islamic University Malaysia P.O. Box: 10, 50728 Kuala Lumpur, Malaysia E-mail: [email protected] Abstract. Path loss models are essential for appropriate wireless network planning as they assist in interference estimations, frequency assignments, and the evaluation of cell parameters. One of the commonly used propagation models is the Lee model which is characterized by its simplicity and good prediction accuracy. This study will estimate the best values for the two parameters of Lee model (γ and L0) which are suitable for suburban environment in Malaysia. The performance of the adjusted Lee model is then compared to the three widely used empirical path loss models which are: Sanford University Interim, COST231 Hata and Egli models. The Root Mean Square Error (RMSE) and the Chi square test (χ2) are used to compare the performance of the four empirical path loss models. The study found that the adjusted Lee model outperforms the other empirical models. Keywords: path loss, wave propagation, empirical models. 1. Introduction Propagation models have traditionally focused on predicting the received signal strength at a given distance from the transmitter, as well as the variability of the signal strength in a close spatial proximity to a particular location [1]. They are very helpful to mobile radio service providers for planning their networks because they allow optimization of the cell coverage while minimizing the intercell interference.
    [Show full text]
  • A Survey on Various Propagation Model for Wireless Communication
    A Survey on Various Propagation Model for Wireless Communication 1Pooja Prajesh and 2R.K. Singh 1Asst. Professor, GRDIMT, Dehradun, India 2Professor, KEC, Dhawarahat, India Abstract The expression of the model Signal Propagation is used for wired or wireless PL(dB)=LF+Amn(f, d)−G(hte)−G(hre)−GAERA (1) communication. It is depend upon terrain, frequency of operation, height of mobile, base station and other dynamic Where factor. Propagation models predict the mean signal strength PL is path loss [dB], LF is Free space path loss [dB] Amn for an arbitrary transmitter-receiver (T-R) separation (f, d) is Median attenuation relative to free space [dB], G(hte) distance[5]. In this paper, Empirical propagation models such is Base station antenna height gain factor [dB], G(hre) is as Okumura, Hata, and Lee model has been surveyed Mobile station antenna height gain factor [dB], GAREA is Gain exhaustively. due to the type of environment [dB], hte: transmitter antenna height [m] hre: Receiver antenna height [m], d is Distance Keywords: Path Loss, Okumura model, Hata model and Lee between transmitter and receiver antenna [km] model G(hre) = 10 log10 (hre/200) hre < 3m G(hre) = 20 log10 (hre/200) 10m> hre >3m G(hte) =20 log10 (hte /3) Introduction In Wireless communication signal is transmitted by Okumura Model is considered to be among the simplest transmitting antenna and received by receiving antenna, any and best in terms of accuracy in predicting the path loss for distortion in signal strength at receiver is known as path loss. early cellular system. The major disadvantages of this model Propagation model are useful for predicting the signal are its slow response to rapid changes in terrain profile.
    [Show full text]