Versatile Two State Model for Land Mobile Satellite Systems: Parameter Extraction and Time Series Synthesis
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Universite´ catholique de Louvain ICTEAM Institute Electrical Engineering Department VERSATILE TWO STATE MODEL FOR LAND MOBILE SATELLITE SYSTEMS: PARAMETER EXTRACTION AND TIME SERIES SYNTHESIS Bel´enMontenegro Villacieros Thesis submitted in partial fulfillment of the requirements for the degree of Docteur en sciences de l'ing´enieur Dissertation committee: Prof. D. Vanhoenacker-Janvier (ICTEAM, UCLouvain, Belgium), adviser Prof. C. Oestges (ICTEAM, UCLouvain, Belgium), secretary Prof. F. P´erez Font´an(UVigo, Spain), member Dr. L. Castanet (ONERA Toulouse, France), member Prof. M. Verleysen (ICTEAM, UCLouvain, Belgium), president September 21, 2011 VERSATILE TWO STATE MODEL FOR LAND MOBILE SATELLITE SYSTEMS: PARAMETER EXTRACTION AND TIME SERIES SYNTHESIS Bel´enMontenegro Villacieros ICTEAM Institute Electrical Engineering Department Universit´ecatholique de Louvain Louvain-la-Neuve (Belgium) A mis padres, a mis hermanos y a mis abuelitos. Contents Acknowledgments xi Abstract xiii Acronyms xv List of Symbols xvii Author's Publication List xxi Introduction xxiii 1 Land Mobile Satellite Systems: General characteristics1 1.1 General Features3 1.1.1 Ionospheric effects3 1.1.2 Tropospheric effects4 1.1.3 Local shadowing and fading effects5 1.2 Components of the signal6 1.2.1 Direct signal component7 1.2.2 Specular reflected component7 1.2.3 Diffuse multipath component8 1.3 Bello functions8 1.4 Doppler characteristics of satellite communication channels 11 1.5 First and Second Order Statistics 13 1.6 Conclusions 15 References 16 2 LMS Propagation Channel Models 17 2.1 Empirical Channel Models 19 2.1.1 Attenuation due to vegetation 19 2.1.2 Models computing the link margin 22 2.2 Deterministic Channel Models 24 2.2.1 Scenario Description 26 vii viii CONTENTS 2.2.2 Ray-tracing and Polarization-tracking 27 2.2.3 Electromagnetic Modelling Using UTD 28 2.2.4 Generation of Results 29 2.3 Statistical Channel Models 31 2.3.1 Global channel modeling 32 2.3.2 State-oriented channel modelling 34 2.4 Physical-Statistical Models 42 2.4.1 Input parameters 42 2.4.2 Time share of shadowing 43 2.4.3 Time Series Model 44 2.5 Conclusions 45 References 49 3 LMS: Measurement Campaigns 53 3.1 ITU-R DBSG3 54 3.1.1 Narrowband parameters 54 3.1.2 Wideband parameters 55 3.2 Global Archive 56 3.2.1 L and S Narrowband Datasets from Bradford University 57 3.2.2 Ka- Band Narrowband Dataset from Joanneum Research 65 3.2.3 Land Mobile Satellite Wideband Measurement Experiment at L and S-Bands from Surrey University 67 3.2.4 Navigation Signal Measurement Campaign for Critical Environments from Joanneum Research 80 3.3 Milady Campaign 86 3.3.1 Description 86 3.3.2 Data Processing 87 3.3.3 Statistical Results 91 3.4 Conclusions 94 References 97 4 LMS: State Markov Models 101 4.1 P´erez-Fontan Three-State Markov Model 103 4.1.1 Model Elements 103 4.1.2 Extraction of Model Parameters 107 4.1.3 Model Limitations 117 4.2 Prieto-Cerdeira Versatile Two-State Model 117 4.2.1 Extraction of Model Parameters 119 CONTENTS ix 4.2.2 Model and Data limitations 121 4.3 Versatile Two-State Model: New and Automatic Parameter Extraction Algorithm 122 4.3.1 Model Parameters 122 4.3.2 New and Automatic Parameter Extraction Algorithm 127 4.3.3 Parameters for S-Band Milady Campaign 182 4.4 Conclusion 183 References 185 5 LMS: Time Series Generators 189 5.1 Existing Time Series Generators 189 5.1.1 P´erez-Fontan Three-State Markov Model Channel Simulator 189 5.1.2 Prieto-Cerdeira Versatile Two-State Model Channel Simulator 191 5.2 New Time Series Generator 195 5.2.1 Simulator Block Diagram 195 5.2.2 Parameters Adjustment and Results Comparisons 206 5.2.3 Model Validation 214 5.2.4 Comparison with 3-State Markov and Versatile Two-State Models 216 5.3 Conclusions 219 References 221 Conclusions 223 Appendix A: Versatile Two-State Model Parameters for S-Band 225 A.1 Urban environment 226 A.2 Suburban environment 228 A.3 Rural environment 231 A.4 Commercial environment 233 A.5 Highway environment 236 Appendix B: Availability of Milady datasets 239 ACKNOWLEDGMENTS A few years ago, I landed at EMIC to start a PhD without knowing how much work, effort and sacrifices would be involved. During all these years, I have passed through different phases of: learning, stressing, facing up to big audiences, organizing big events and many other situations. Going through all these different phases would not have been possible without the help of all the people I acknowledge here. To begin, I want to thank first and foremost my adviser Prof. Danielle Vanhoenacker-Janvier. She was the person who offered me the opportunity to realize my PhD and who welcomed me warmly in the lab. During these years, she always supported me with her wise and calm advice and believed in my potential by allowing me to participate in European Space Agency and Euro- pean Union projects and to become the Belgium Delegate in the International Telecommunications Union Radiocommunications Sector. Thank you very much. I would also like to thank Prof. Claude Oestges, for the nice technical discus- sions that were very helpful to take decisions throughout my PhD. I am also fully in debt to Prof. Fernando P´erezFont´anfor receiving me at Vigo University during one week to work on the model, for his support and involvement in my PhD. I am very honored by the distinguished members of the thesis examina- tion committee. I would like to thank my adviser Prof. Danielle Vanhoenacker- Janvier, the secretary Prof. Claude Oestges, the external members Dr. Laurent Castanet and Prof. Fernando P´erezFont´anand the president Prof. Verleysen. Thank you all for having read my text with interest. Your questions and com- ments helped me to improve it significantly. I would like to take the opportunity to thank Roberto Prieto Cerdeira from ESA/ESTEC for receiving me at ESTEC during one week to discuss and work on the model. Special thanks to Ernst Eberlein, Thomas Heyn and Daniel Arndt from Faun- hofer Institute, for having given me the access to the valued datasets from the Milady experimental campaign. At UCL, I am very thankful to my colleagues for the nice and pleasant work- ing environment and for their friendship: St´ephanieEggermont, Isabel Molen- berg, Dragos Dancila, Judith Spiegel, Julio C´esarTinoco, Carlos Pereira, Kahina Djafri, Ibtissem Oueriemi, Maribel Rocha, Ester Tooten, David Sp^ot,Mostafa Emam, Samer Houri, C´esarRoda Neve, Fran¸oisHubin, Beno^ıtOlbrechts, Olivie Renaudin, Francesco Mani, Pascal Simon, Marie-Christine Vandingenen, Isabelle Dargent, Prof. Isabelle Huynen and Prof. Jean-Pierre Raskin. xi xii I would like to thank my Spanish expatriate friends, for they care and un- derstanding: Estela Juli´an,Sergio Zapardiel, Sonia Esteban, Erik Hengmith and Sergio Serrano, and my Spanish non expatriate friends for the distance support through these years: Patricia Delgado, Zahara Lopez, Luisa Vaquero, Cristina Casal, Catuxa Torell, Marta Ruiz and Luis Jare~no. I also thank my dear J´er^omefor his care and love. Tous mes remerciements `ama famille de Chamonix pour son soutien: J´er^ome Marx, Jocelyne et sœurs Couttet, Philipphe Chevalier, Tito, Camille et Maxime Marx. Me gustaria agradecerle a mi familia el apoyo que me han dado durante todo este tiempo desde la distancia. Finalmente, quer´ıadedicar este texto a mis padres, a mis hermanos y a mis abuelitos, que gracias a su apoyo, a su amor incondicional y todo lo que han hecho por mi durante estos a~nos,ha hecho posible llevar el barco a buen puerto. Bel´en Louvain la Neuve, September 2011 ABSTRACT A Land Mobile Satellite System (LMSS) is a satellite-based communication system that provides voice and data communications services as Internet, tele- phone, radio, TV, etc., to terrestrial mobile users. These kind of wireless commu- nications services have had a great success in the past few years and they have become essential on people's everyday lives around the world. Whereas in the early days of mobile communications Quality of Service (QoS) was often poor, nowadays it is assumed the service will be ubiquitous, of high speech quality and the ability to watch and share streaming video or even broadcast television pro- grams for example, is driving operators to offer even higher uplink and downlink data-rates, while maintaining appropriate QoS. LMSS offers the benefits of true global coverage, reaching into remote areas as well as populated areas, whereas terrestrial mobile communications infras- tructure, even if it has made deep inroads, there are still geographically remote and isolated areas without good coverage, and several countries do not yet have coverage in towns and cities. Current terrestrial mobile communication systems are inefficient in the de- livery of multicast and broadcast traffic. Satellite based mobile communications offers great advantages in delivering multicast and broadcast traffic because of their intrinsic broadcast nature. The utilization of satellites to complement ter- restrial mobile communications for bringing this type of traffic to the mass mar- ket is gaining increasing support in the standards groups, as it may well be the cheapest and most efficient method of doing so. In a LMSS, the signal information travels from the satellite to the final moving terminal at the Earth. Furthermore, before arriving at the terminal, the signal propagates across the ionosphere and the troposphere causing impairments to the wave. Terrain, trees and buildings will cause the main distortions in the signal. All the impairments and distortions need to be characterized in order to understand the propagation phenomena affecting the channel, and to develop propagation models obtaining rules to relate these phenomena to the frequency, speed between the satellite and the mobile terminal, elevation angle or type of antenna.