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UNIVERSITY OF CINCINNATI Date:___________________ I, _________________________________________________________, hereby submit this work as part of the requirements for the degree of: in: It is entitled: This work and its defense approved by: Chair: _______________________________ _______________________________ _______________________________ _______________________________ _______________________________ Modeling and Performance Analysis of Mobile Ad Hoc Networks A dissertation submitted to the Division of Graduate Studies and Research of The University of Cincinnati In partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY In the Department of Electrical & Computer Engineering and Computer Science of the College of Engineering by Xiaolong Li M.E., (EE), Huazhong University of Science & Technology, China, 2002. B.E., (EE), Huazhong University of Science & Technology, China, 1999. Thesis Advisor and Committee Chair: Dr. Qing-An Zeng February 23, 2006 Abstract Ad hoc networks are gaining increasing popularity in recent years because of their ease of deployment. No wired base station or infrastructure is supported, and each host communicates one another via packet radios. In ad hoc networks, nodes are mobile which bring many challenges, such as network connectivity, topology change, link characteristic, and etc. In this research work, a novel model to analyze the link stability in mobile ad hoc networks is proposed. In the proposed analytical model, between each communicating pair, one node is considered to be stationary while the other moves relative to it. With this method, the mobility models defined in this dissertation can be approximated as a fluid flow model. Using the result of the fluid flow model, the analytical model for the link duration is obtained, which is used to obtain the link holding time and the link breaking probability of a communicating pair. The distribution of a routing path duration and the routing path breaking probability are also obtained by extending the models of the link duration and the link breaking probability. These results of link and routing path stabilities are serviced as ground knowledge to obtain the performance of medium access control (MAC) protocol considering node mobility. 1 MAC protocols are a fundamental element that determines the efficiency in sharing the limited communication bandwidth of wireless channels. IEEE 802.11 distributed coordination function (DCF) MAC protocol is the most widely used MAC protocol in ad hoc networks due to its compatibility with the IEEE 802 protocol suite. Since the release of the IEEE 802.11 standard, many research efforts have been devoted to modeling the performance of this protocol. However, most of studies are confined to the stationary performance where the nodes are immobile. In this research work, we employ the link and routing path stability models to analyze the performance of the IEEE 802.11 DCF MAC protocol in dynamic environment. To the best of our knowledge, this is the first time to evaluate the performance of this protocol with mobility. Another contribution of this research work is to analyze the performance of the IEEE 802.11 DCF MAC protocol with capture effect. Currently, most analytical models assume that all received packets at the receiver have the same physical conditions (same power, same coding, etc), so when two or more nodes transmit their packets at the same time, the collision happens and all packets involved are destroyed, which may not be the case in reality due to capture effect. In this research work, we provide an analytical model to obtain the probability of capture effect. We use this probability of capture effect to analyze the throughput of the IEEE 802.11 DCF MAC protocol in ad hoc networks considering path loss, multipath fading, and shadowing. Wireless channel is time-varying and error prone. The packet transmission can be failed due to transmission errors. In this research work, a refined analytical 2 model is presented to evaluate the performance of the IEEE 802.11 DCF MAC protocol with time-varying wireless channel. In the proposed model, the time- varying wireless channel is modeled by a finite-state Markov (FSM) chain. In each channel state, the operation of the IEEE 802.11 DCF MAC protocol is modeled by an embedded Markov chain. Using this model, the throughput of the DCF protocol can be theoretically calculated. The results show that the performance of the DCF protocol strongly depends on the network size, the incoming traffic loads, and the bit error rate (BER). When the incoming traffic load is light, the throughput increases when the network size grows. When the network works under heavy (saturated) condition, the throughput decreases when the network size grows. The throughput always degrades when increasing BER regardless the network size and the traffic load. 3 Acknowledgements I am most grateful and indebted to my advisor, Professor Qing-An Zeng, for the large doses of guidance, patience, and encouragement he has shown me during my time here at The University of Cincinnati. He always found time whenever I needed an intelligent discussion. It is a pleasure, as well as a honor, to work with him. I am also grateful and indebted to Professor Dharma Agrawal, for inspiration and enlightening discussions on a wide variety of topics. I thank my other committee members, Professor Anca Ralescu, Professor James Caffery, and Professor Heng Wei, for their insightful commentary on my work. Also, I would like to extend my gratitude to the department staff members. My special thanks to Julie Muenchen and Teresa Hamad for making sure I stay out of trouble. Finally, I would like to express my deepest gratitude to my family and friends. I thank Duojia Zhu, my wife, who has been an endless source of encouragement and support through the most trying of times. I would like to extend my endless gratitude and love to my parents, without whom I would never have been able to think of embarking on such a journey. i Table of Contents 1 Introduction 1 1.1 Background and Motivation . 1 1.1.1 Wireless Local Area Networks . 1 1.1.2 Challenges in Ad Hoc Networks . 3 1.2 Contributions . 7 1.3 Organization of the dissertation . 8 1.4 Summary . 8 2 Overview of Mobility Models and MAC Protocols 9 2.1 Introduction . 9 2.2 Mobility Models . 10 2.2.1 Independent Mobility Models . 10 2.2.2 Group Mobility Models . 14 2.2.3 Other Mobility Parameters . 15 2.3 MAC Protocols . 15 2.3.1 Carrier Sense Multiple Access . 16 2.3.2 Multiple Access with Collision Avoidance . 16 ii 2.3.3 Floor Acquisition Multiple Access . 17 2.3.4 IEEE 802.11 Distributed Coordination Function . 18 2.4 Summary . 20 3 Link and Routing Path Stabilities in Mobile Ad Hoc Networks 21 3.1 Introduction . 21 3.2 System Model . 23 3.3 Analysis of Node Motion . 25 3.4 Analysis of Link Characteristics . 26 3.4.1 Link Duration . 27 3.4.2 Link Holding Time . 29 3.4.3 Link Breaking Probability . 30 3.5 Simulations and Discussions . 32 3.6 Summary . 39 4 Performance Analysis of MAC Protocol in Mobile Ad Hoc Net- works 41 4.1 Introduction . 41 4.2 Single-hop Ad Hoc Networks . 43 4.2.1 System Model . 43 4.2.2 Performance Analysis . 44 4.3 Multi-hop Ad Hoc Networks . 52 4.3.1 System Model . 52 4.3.2 Performance Analysis . 53 iii 4.4 Simulations and Discussions . 59 4.5 Summary . 61 5 Impact of Capture Effect on the Performance of MAC Protocol 63 5.1 Introduction . 63 5.2 Channel Model . 65 5.3 Capture Model . 67 5.4 Analytical Model . 70 5.5 Numerical Results and Discussions . 72 5.6 Summary . 76 6 Influence of Time-varying Channel on the Performance of MAC Protocol 79 6.1 Introduction . 79 6.2 Wireless Channel Model . 81 6.3 Analytical Model . 84 6.4 Numerical Results and Discussions . 89 6.5 Summary . 91 7 Conclusions and Future Work 94 7.1 Conclusions . 94 7.2 Future Work . 97 iv List of Figures 2.1 Illustration of hidden node problem . 17 2.2 Illustration of exposed node problem . 18 2.3 Basic CSMA/CA Protocol . 20 2.4 CSMA/CA with RTS/CTS protocol . 20 3.1 System model . 24 3.2 pdfs of link duration . 34 3.3 pdfs of routing path duration . 35 3.4 pdfs of link holding time . 37 3.5 Link breaking probability versus average virtual packet transmission time . 38 3.6 Routing path breaking probability versus average speed . 40 4.1 Embedded slots . 46 4.2 Markov chain model for the entire network . 46 4.3 Structure of time Tv .......................... 51 4.4 System model . 53 4.5 Illustration of hidden area . 54 v 4.6 Throughput of CSMA/CA protocol . 60 4.7 Throughput for basic CSMA/CA . 61 4.8 Throughput for CSMA/CA with RTS/CTS . 61 5.1 Spatial distribution of two arbitrary nodes in ad hoc networks . 66 5.2 pdf of distance R between any two nodes in ad hoc networks . 67 5.3 Capture probability in infrastructure mode (σs = 1.35) . 73 5.4 Capture probability in ad hoc mode (σs = 1.35) . 73 5.5 Capture probability in infrastructure mode (σs = 1.35) . 74 5.6 Capture probability in an ad hoc mode (σs = 1.35) . 74 5.7 Throughput of basic CSMA/CA versus traffic load G with capture model of the first category . 75 5.8 Throughput of CSMA/CA with RTS/CTS versus traffic load G with capture model of the first category . 76 5.9 Throughput of basic CSMA/CA versus traffic load G with capture model of the second category . 77 5.10 Throughput of CSMA/CA with RTS/CTS versus traffic load G with capture model of the second category .