Principles of the Complete Voronoi Diagram Localization

This paper explores the rationale behind the Complete Voronoi Diagram (CVD) Localization, which is a computational geometry approach to the wireless network localization. Our work consists mainly of three parts. The first part focuses on the analysis of CVD's mathematical properties. We characterize CVD's central tendency as the mirror-image distribution and provide mathematical formula for its probability density function. We also provide a closed formula for the relationship between CVD's vertices, chords, and faces, the average chord length, and the average edge number of a CVD polygon. And, the expressions for the average overall and local positioning error are also provided. Based upon these findings, we show that the convergence speed for a CVD based localization scheme is quadratic, and the optimal time and space complexities are Θ(n2) and Θ(n), respectively. The second part proposes a novel approach, called Polling, which utilizes the concept of the Error Region, to further improve the accuracy. Polling, in theory, enables us to make use of the topology information with the quantity up to O(n4) provided by CVD for localization, while a conventional CVD scheme can use only O(1) such information. The third part, through simulations, shows how to use the quasi Analog-to-Digital Conversion (qADC) strategy to handle signal errors. Combined with Polling and qADC, a CVD scheme can provide a simple, robust, and powerful solution to the wireless network localization. Some of our findings and methods may also contribute to the field of computational geometry its own.

[1]  Yunhao Liu,et al.  Beyond Trilateration: On the Localizability of Wireless Ad Hoc Networks , 2009, IEEE/ACM Transactions on Networking.

[2]  Mani B. Srivastava,et al.  Dynamic fine-grained localization in Ad-Hoc networks of sensors , 2001, MobiCom '01.

[3]  Gang Zhou,et al.  Models and solutions for radio irregularity in wireless sensor networks , 2006, TOSN.

[4]  Ning Ruan,et al.  Global optimal solutions to general sensor network localization problem , 2014, Perform. Evaluation.

[5]  Gerhard P. Hancke,et al.  Ultrawideband as an Industrial Wireless Solution , 2006, IEEE Pervasive Computing.

[6]  Tarek F. Abdelzaher,et al.  Range-free localization and its impact on large scale sensor networks , 2005, TECS.

[7]  Qiang Yang,et al.  Learning Adaptive Temporal Radio Maps for Signal-Strength-Based Location Estimation , 2008, IEEE Transactions on Mobile Computing.

[8]  Shih-Hau Fang,et al.  Indoor Location System Based on Discriminant-Adaptive Neural Network in IEEE 802.11 Environments , 2008, IEEE Transactions on Neural Networks.

[9]  Ying Zhang,et al.  Localization from mere connectivity , 2003, MobiHoc '03.

[10]  Venkata N. Padmanabhan,et al.  Indoor localization without the pain , 2010, MobiCom.

[11]  Xiang-Yang Li,et al.  SmartLoc: push the limit of the inertial sensor based metropolitan localization using smartphone , 2013, MobiCom.

[12]  L. El Ghaoui,et al.  Convex position estimation in wireless sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[13]  Lei Yang,et al.  Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices , 2014, MobiCom.

[14]  Kaveh Pahlavan,et al.  Measurement and Modeling of Ultrawideband TOA-Based Ranging in Indoor Multipath Environments , 2009, IEEE Transactions on Vehicular Technology.

[15]  Lu Wang,et al.  NomLoc: Calibration-Free Indoor Localization with Nomadic Access Points , 2014, 2014 IEEE 34th International Conference on Distributed Computing Systems.

[16]  Anshul Rai,et al.  Zee: zero-effort crowdsourcing for indoor localization , 2012, Mobicom '12.

[17]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) using AOA , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[18]  Yunhao Liu,et al.  Swadloon: Direction Finding and Indoor Localization Using Acoustic Signal by Shaking Smartphones , 2015, IEEE Transactions on Mobile Computing.

[19]  Bhaskar Krishnamachari,et al.  Sequence-Based Localization in Wireless Sensor Networks , 2008, IEEE Transactions on Mobile Computing.

[20]  Moe Z. Win,et al.  Impulse radio: how it works , 1998, IEEE Communications Letters.

[21]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[22]  Theodore S. Rappaport,et al.  Wireless Communications: Principles and Practice (2nd Edition) by , 2012 .

[23]  Lei Yang,et al.  Anchor-free backscatter positioning for RFID tags with high accuracy , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[24]  Ismail Güvenç,et al.  A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques , 2009, IEEE Communications Surveys & Tutorials.

[25]  John A. Stankovic,et al.  Kinsight: Localizing and Tracking Household Objects Using Depth-Camera Sensors , 2012, 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems.

[26]  Ross A. Knepper,et al.  RF-compass: robot object manipulation using RFIDs , 2013, MobiCom.

[27]  Zhi Ding,et al.  Distance Estimation From Received Signal Strength Under Log-Normal Shadowing: Bias and Variance , 2008, IEEE Signal Processing Letters.

[28]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[29]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[30]  Gaetano Borriello,et al.  SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength , 2000 .

[31]  Monica Nicoli,et al.  A Jump Markov Particle Filter for Localization of Moving Terminals in Multipath Indoor Scenarios , 2008, IEEE Transactions on Signal Processing.

[32]  Jue Wang,et al.  Dude, where's my card?: RFID positioning that works with multipath and non-line of sight , 2013, SIGCOMM.

[33]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..

[34]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[35]  Yunhao Liu,et al.  Montage: Combine Frames with Movement Continuity for Realtime Multi-User Tracking , 2014, IEEE Transactions on Mobile Computing.

[36]  Brian D. O. Anderson,et al.  A Theory of Network Localization , 2006, IEEE Transactions on Mobile Computing.

[37]  G. Dileep Kumar,et al.  Localization of Mobile Nodes in Wireless Networks with Correlated in Time Measurement Noise , 2012 .

[38]  Mani B. Srivastava,et al.  The bits and flops of the n-hop multilateration primitive for node localization problems , 2002, WSNA '02.

[39]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[40]  Moe Z. Win,et al.  Power Optimization for Network Localization , 2013, IEEE/ACM Transactions on Networking.

[41]  Jana Kosecka,et al.  Vision based topological Markov localization , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[42]  Yunhao Liu,et al.  Localization of Wireless Sensor Networks in the Wild: Pursuit of Ranging Quality , 2013, IEEE/ACM Transactions on Networking.

[43]  Min Gao,et al.  FILA: Fine-grained indoor localization , 2012, 2012 Proceedings IEEE INFOCOM.

[44]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[45]  KatabiDina,et al.  Dude, where's my card? , 2013 .

[46]  B. T. Fang,et al.  Simple solutions for hyperbolic and related position fixes , 1990 .