Eindhoven University of Technology MASTER Facilitating wireless coexistence research Kulkarni, V.M. Award date: 2015 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. 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Anwar Hithnawi Prof. Dr. Friedemann Mattern Dr. Majid Nabi Najafabadi Registration Date: March 1, 2015 Submission Date: August 17, 2015 Declaration of Originality I hereby declare that this written work I have submitted is original work which I alone have authored and which is written in my own words. With the signature I declare that I have been informed regarding normal academic citation rules and that I have read and understood the information on \Citation etiquette": http://www.ethz.ch/students/exams/plagiarism_s_en.pdf The citation conventions usual to the discipline in question here have been respected. This written work may be tested electronically for plagiarism. Zurich, August 17, 2015 Vaibhav Kulkarni iii Abstract The past decade has seen a rapid growth in the number of wireless technologies and devices. The unlicensed bands host a range of heterogeneous RF radios which compete with each other for the shared channel access and give rise to non trivial communication challenges such as Cross-Technology-Interference (CTI), co-existence and achieving fairness. Thus, there is a growing need in the research community today, to understand and debug the network performance in the presence of CTI. In this thesis, we address wireless coexistence by focusing on designing tools to facilitate repeatable and controllable interference generation and investigating algorithms to localize high power interference sources in indoor wireless networks. We design a platform to generate controllable interference patterns depicted by prevalent interference sources active in 2.4 GHz ISM band. This tool provides three interfaces consisting of a record and playback module to generate interference pat- terns of sources which are not typically RF radios, a software radio implementation module consisting of implementations of consumer wireless devices and a commercial radio chipset module to generate interference depicted by prevalent communication protocols. The unified nature of this tool makes it easy to integrate in testbeds and operate remotely. We validate the accuracy of the generated interference patterns in the temporal and spectral domains and quantify the impact on communication links. We achieve high accuracy and realism for interferer types occupying narrow band- width such as analog phone and interferers depicting frequency sweeping behavior such as microwave oven. In order to troubleshoot the network performance, it is as well beneficial to localize the interference source degrading the network throughput. To this end, we design and implement an algorithm to localize rouge interfering radios using a low power wireless network. Prior work on localizing uncooperative radios is restricted to WiFi networks, where, off the shelf WiFi cards having reasonable computational capability and multiple antennas have been used. Our design addresses the challenges offered by low-power senor nodes, such as low computational capability, lower sampling rates and a single omnidirectional antenna. It exploits the collaborative and distributed nature of a dense network to model the propagation loss characteristics of the medium in order to mask the ill effects of multipath and shadowing in an indoor environment. We observe that, the localization accuracy is dependent upon the interferer type and achieve an average point level accuracy of 2.1 meters. v Acknowledgements Hereby, I would like to express my sincere gratitude to those who helped and supported me during this mater thesis work and particularly thank: My supervisors Prof. Friedemann Mattern and Dr. Majid Nabi Najafabadi for their valuable suggestions and feedbacks. My advisor Anwar Hithnawi for all the constructive discussions, insightful comments, patient tutoring and proofreading my thesis. I also thank Hossein Shafagh for the interesting discussions about upcoming technical developments and for providing help whenever I faced difficulties in the technical fronts. I thank Dr. Vlado Handziski for providing the testbed access and help in conducting experiments. My lab mates, Su and Dominic for all the interesting discussions and help. All my friends at CRS for providing such a wonderful time in Zurich. I thank Zeno Karl Schindler foundation for providing the grant for my master thesis. Distributed Systems Group at ETH for the motivating and friendly working atmo- sphere. Last but not the least my family for always being there. vii Contents 1 Introduction 1 2 Background 3 2.1 Wireless Communication . .3 2.1.1 Communication Systems . .3 2.1.2 Digital Modulation and Spread Spectrum Techniques . .5 2.1.3 Multipath Fading and Shadowing . .7 2.1.4 Interference . .8 2.2 Low-Power Wireless Networks . .9 2.2.1 Technologies and Application . .9 2.2.2 Overview of IEEE 802.15.4 . 10 2.3 Localization and Position Estimation . 11 2.3.1 Range Based Localization . 12 2.3.2 Range Free Localization . 15 2.4 Toolkits and Devices . 16 2.4.1 Software Defined Radios . 16 2.4.2 Wireless Sensor Networks and Testbeds . 18 2.4.3 Operating Systems for Constrained Devices . 19 2.4.4 Sensor Network Platforms . 20 3 Related Work 21 3.1 Controllable Interference Generation . 21 3.1.1 WiFi Based Technique . 21 3.1.2 Packet Storming . 21 3.1.3 Radio Test Modes . 22 3.1.4 Limitations of Current Techniques . 23 3.2 Localizing Interfering Radios in Wireless Networks . 24 3.2.1 PinPoint Approach . 24 3.2.2 WiFiNet Approach . 25 4 CIG Design and Implementation 27 4.1 Motivation . 27 4.2 Interference Characteristics . 27 4.3 Design Overview . 32 4.4 Implementation . 34 4.4.1 Record and Playback Interface . 34 ix Contents 4.4.2 Software Radio Implementation Interface . 39 4.4.3 Commercial Radio Chipset Interface . 44 5 CIG Performance Evaluation 47 5.1 Temporal Accuracy . 47 5.2 Spectral Accuracy . 49 5.3 Impact on Communication Link . 50 6 Localizing Interfering Radios - Design and Implementation 57 6.1 Iterative Search Localization Design . 57 6.2 Implementation . 62 7 Localization Accuracy 73 7.1 Error Estimation . 73 7.2 Comparison of Localization Approaches . 74 8 Conclusion 79 9 Future Work 81 Bibliography 83 A First Appendix 93 x 1 Introduction The rapid growth and proliferation in the number of wireless devices operating around us is causing congestion in the unlicensed spectrum. The 2.4 GHz ISM band is occupied by prevalent technologies such as WiFi (IEEE 802.11) [5], Bluetooth [27], IEEE 802.15.4 [16], analog and digital cordless phones, security cameras and 2.4 GHz RFID. These heterogeneous RF radios follow different protocols, communication primitives and have diverse physical layer artifacts. Such devices coexist and compete for the shared channel access leading to Cross-Technology-Interference (CTI). CTI has adverse effects on the performance wireless technologies and results in packet losses, increased network latency and reduced energy efficiency. In addition, CTI also has severe effects on the performance of RF based services such as indoor localization [33, 45] and activity recognition systems [18, 20]. Interference is the major cause today for reducing the network throughput and thus there is a strong need for understanding and debugging the performance of wireless networks under CTI. Problem Statement In order to improve the performance and robustness of the wireless systems it is necessary to gain a detailed understanding of how the heterogeneous devices coexist and compete in the shared ISM band. Further, it is also necessary to perceive, how the CTI sources affect the communication parameters such as error patterns, channel back-offs, packet corruption rates and others. This study, requires an infrastructure to generate repeatable and controllable interference patterns which can be used to augment the testing environments in order to expose networks to realistic interference. Currently, researchers working with wireless coexistence use either modeling or simulation [49,67] which are inaccurate and abstract. On the other hand, some researchers use the interference generated from actual wireless devices [23,55], which is realistic but cumbersome, expensive and impractical.