high resolution time-of-arrival ranging of wireless sensor nodes in non-homogenous environments

195 Pages·2017·7.36 MB·English

MMiicchhiiggaann TTeecchhnnoollooggiiccaall UUnniivveerrssiittyy
DDiiggiittaall CCoommmmoonnss @@ MMiicchhiiggaann TTeecchh
Dissertations, Master's Theses and Master's Reports
2016
HHIIGGHH RREESSOOLLUUTTIIOONN TTIIMMEE--OOFF--AARRRRIIVVAALL RRAANNGGIINNGG OOFF WWIIRREELLEESSSS
SSEENNSSOORR NNOODDEESS IINN NNOONN--HHOOMMOOGGEENNOOUUSS EENNVVIIRROONNMMEENNTTSS
Mohsen Jamalabdollahi
Michigan Technological University, [email protected]
Copyright 2016 Mohsen Jamalabdollahi
RReeccoommmmeennddeedd CCiittaattiioonn
Jamalabdollahi, Mohsen, "HIGH RESOLUTION TIME-OF-ARRIVAL RANGING OF WIRELESS SENSOR
NODES IN NON-HOMOGENOUS ENVIRONMENTS", Open Access Dissertation, Michigan Technological
University, 2016.
https://doi.org/10.37099/mtu.dc.etdr/268
Follow this and additional works at: https://digitalcommons.mtu.edu/etdr
Part of the Signal Processing Commons
HIGH RESOLUTION TIME-OF-ARRIVAL RANGING OF WIRELESS SENSOR
NODES IN NON-HOMOGENOUS ENVIRONMENTS
By
Mohsen Jamalabdollahi
A DISSERTATION
Submitted in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
In Electrical Engineering
MICHIGAN TECHNOLOGICAL UNIVERSITY
2016
Copyright 2016 Mohsen Jamalabdollahi

This dissertation has been approved in partial fulfillment of the requirements for
the Degree of DOCTOR OF PHILOSOPHY in Electrical Engineering.
Department of Electrical and Computer Engineering
Dissertation Advisor: Prof. Seyed (Reza) Zekavat
Committee Member: Prof. Daniel Fuhrmann
Committee Member: Dr. Zhaohui Wang
Committee Member: Dr. Alexander Labovsky
Department Chair: Prof. Daniel Fuhrmann

Dedication
To my Beloved parents
who’s the first priority were their children success.

Contents
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Wireless Sensor Network Localization . . . . . . . . . . . . . . . . 1
1.2 Applications of Localization in Non-Homogenous Media . . . . . . 4
1.2.1 Applications in Environmental Monitoring and Remote Sens-
ing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.2 Applications in Health Care . . . . . . . . . . . . . . . . . 5
1.3 Time-of-ArrivalandOrthogonalFrequencyDivisionMultipleAccess 7
1.3.1 Time-of-Arrival Estimation . . . . . . . . . . . . . . . . . 7
1.3.2 Orthogonal Frequency Division Multiple Access (OFDMA) 9
1.4 Chapters Contributions . . . . . . . . . . . . . . . . . . . . . . . . 10
vii
2 Joint Neighbor Discovery and ToA Estimation in Wireless Sensor
Networks via OFDMA . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3 Joint ND and ToA Estimation . . . . . . . . . . . . . . . . . . . . 21
2.3.1 Neighbor Discovery . . . . . . . . . . . . . . . . . . . . . . 22
2.3.2 ToA Estimation . . . . . . . . . . . . . . . . . . . . . . . . 27
2.3.3 Impact of the Number of Sub-Carriers . . . . . . . . . . . 31
2.4 Experimental Challenges . . . . . . . . . . . . . . . . . . . . . . . 34
2.4.1 Energy Efficiency and Scalability . . . . . . . . . . . . . . 34
2.4.2 OFDMA Limitations . . . . . . . . . . . . . . . . . . . . . 37
2.4.2.1 SFO and CFO . . . . . . . . . . . . . . . . . . . 37
2.4.2.2 PAPR . . . . . . . . . . . . . . . . . . . . . . . . 38
2.5 Simulation Results and Discussion . . . . . . . . . . . . . . . . . . 39
2.5.1 Simulation Parameters and Methods . . . . . . . . . . . . 39
2.5.2 Neighbor Discovery Performance . . . . . . . . . . . . . . 41
2.5.3 ToA Estimation Performance . . . . . . . . . . . . . . . . 44
2.5.4 Energy Efficiency and Scalability Analysis . . . . . . . . . 50
2.6 Conclusions and Future Works . . . . . . . . . . . . . . . . . . . . 51
2.6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
2.6.2 Future Works and Discussion . . . . . . . . . . . . . . . . 52
viii
3 High Resolution ToA Estimation via Optimal Waveform Design 53
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.2 System Model and Problem Formulation . . . . . . . . . . . . . . 56
3.3 Proposed Technique . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.3.1 Maximum rising level Detector . . . . . . . . . . . . . . . 60
3.3.2 Waveform Design . . . . . . . . . . . . . . . . . . . . . . . 66
3.3.2.1 Forming the objective function . . . . . . . . . . 66
3.3.2.2 Trust-region Algorithm . . . . . . . . . . . . . . . 68
3.4 Simulation Results and Discussion . . . . . . . . . . . . . . . . . . 72
3.4.1 Simulation Parameters and Methods . . . . . . . . . . . . 72
3.4.2 ToA Estimation Performance . . . . . . . . . . . . . . . . 73
3.4.3 Complexity Analysis vs Performance . . . . . . . . . . . . 75
3.4.4 ToA CRLB . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4 High Resolution ToA Estimation in Non-homogenous, Frequency
Dispersive Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.2 Proposed ToA Estimation Technique . . . . . . . . . . . . . . . . 88
4.2.1 Time Frame Detection Technique . . . . . . . . . . . . . . 89
4.2.2 High Resolution ToA Estimation . . . . . . . . . . . . . . 91
4.3 Simulations Result and Discussions . . . . . . . . . . . . . . . . . 103
ix