Distributed Mobility Tracking for Ad Hoc Networks Based on an Autoregressive Model

In ad hoc networks, node mobility causes the network topology to change dynamically over time, which complicates important tasks such as routing and flow control. We propose a distributed scheme for accurately and efficiently tracking the mobility of nodes in ad hoc networks. A first-order autoregressive model is used to represent the evolution of the mobility state of each node, which consists of position, velocity, and acceleration. Each node uses an extended Kalman filter to estimate its mobility state by incorporating network-based signal measurements and the position estimates of the neighbor nodes. Neighbor nodes exchange their position estimates periodically by means of HELLO packets. Each node re-estimates its mobility model parameters, allowing the scheme to adapt to changing mobility characteristics. In practice, a small number of reference nodes with known coordinates is required for accurate mobility tracking. Simulation results validate the accuracy of the proposed tracking scheme.

[1]  Tong Liu,et al.  Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks , 1998, IEEE J. Sel. Areas Commun..

[2]  R. Singer.  Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets , 1970, IEEE Transactions on Aerospace and Electronic Systems.

[3]  Brian L. Mark,et al.  Real-time mobility tracking algorithms for cellular networks based on Kalman filtering , 2005, IEEE Transactions on Mobile Computing.

[4]  Gordon L. Stuber,et al.  Principles of Mobile Communication , 1996 .

[5]  Christian Bettstetter,et al.  Smooth is better than sharp: a random mobility model for simulation of wireless networks , 2001, MSWIM '01.

[6]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..

[7]  Srdjan Capkun,et al.  GPS-free Positioning in Mobile Ad Hoc Networks , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[8]  Mingyan Liu,et al.  Random waypoint considered harmful , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[9]  James J. Caffery,et al.  Wireless Location in CDMA Cellular Radio Systems , 1999 .

[10]  Brian L. Mark,et al.  A mobility tracking model for wireless ad hoc networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[11]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[12]  H. Vincent Poor,et al.  An Introduction to Signal Detection and Estimation , 1994, Springer Texts in Electrical Engineering.

[13]  H. Vincent Poor,et al.  An introduction to signal detection and estimation (2nd ed.) , 1994 .

[14]  J. Woods,et al.  Probability and Random Processes with Applications to Signal Processing , 2001 .

[15]  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).

[16]  Hing Cheung So,et al.  Performance of TOA-AOA Hybrid Mobile Location , 2003, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[17]  Imrich Chlamtac,et al.  A distance routing effect algorithm for mobility (DREAM) , 1998, MobiCom '98.

[18]  Brian L. Mark,et al.  Mobility estimation for wireless networks based on an autoregressive model , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[19]  Nitin H. Vaidya,et al.  Location-aided routing (LAR) in mobile ad hoc networks , 1998, MobiCom '98.

[20]  Prithwish Basu,et al.  A mobility based metric for clustering in mobile ad hoc networks , 2001, Proceedings 21st International Conference on Distributed Computing Systems Workshops.

[21]  Andrey V. Savkin,et al.  Mobility modelling and trajectory prediction for cellular networks with mobile base stations , 2003, MobiHoc '03.

[22]  Srdjan Capkun,et al.  Self-organization in mobile ad hoc networks: the approach of Terminodes , 2001, IEEE Commun. Mag..

[23]  M. Gudmundson.  Correlation Model for Shadow Fading in Mobile Radio Systems , 1991 .

[24]  Brian L. Mark,et al.  Robust mobility tracking for cellular networks , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[25]  Jae S. Lim,et al.  Advanced topics in signal processing , 1987 .

[26]  R. Moose,et al.  Modeling and Estimation for Tracking Maneuvering Targets , 1979, IEEE Transactions on Aerospace and Electronic Systems.