Range-Based Relative Velocity Estimations for Networked Mobile Devices

The relative velocity between mobile devices is one of the key factors that determine the quality of communications in Mobile Ad-hoc NETworks (MANETs). Velocity estimates are useful in various aspects of ad hoc networking (e.g., predicting link lifetime and measuring performance). Conventional ways of estimating velocity rely on the availability of positioning systems such as the Global Positioning System (GPS) or precise knowledge of the characteristics of wireless channels/signals. A recently proposed method exploits time-varying internode range information for velocity estimations, provided that the range estimates are noise free. In this paper, we propose a new range-based method for relative velocity estimations (RVEs). We derive two range-based relative velocity estimators for both sparse and dense ad hoc networks, i.e., RVEs and RVEd. In addition to being less dependent on the characteristics of the wireless channel, the proposed method is more tolerant of the multipath or nonline-of-sight (NLOS) errors contained in range measurements than the existing method. Simulation results show an excellent match between the velocity estimates given by the proposed method and the actual values in both sparse and dense network cases, regardless of the nodal speed limits or the distribution of noises. In comparison with the existing method, the proposed method is shown to achieve an improvement factor of about 33 (in terms of normalized bias) with Gaussian multipath noises of 4-m standard deviation or 20 with uniform NLOS noises of 32-m maximum standard deviation.

[1]  Donald C. Cox,et al.  Estimation of mobile speed and average received power in wireless systems using best basis methods , 1999, Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020).

[2]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[3]  Elmar Gerhards-Padilla,et al.  BonnMotion: a mobility scenario generation and analysis tool , 2010, SimuTools.

[4]  Boualem Boashash,et al.  Mobile unit velocity estimation based on the instantaneous frequency of the received signal , 2004, IEEE Transactions on Vehicular Technology.

[5]  Christian Bettstetter,et al.  On the Connectivity of Ad Hoc Networks , 2004, Comput. J..

[6]  Jan C. Olivier,et al.  Mobile speed estimation for TDMA-based hierarchical cellular systems , 2001, IEEE Trans. Veh. Technol..

[7]  Jean-Yves Le Boudec,et al.  Perfect simulation and stationarity of a class of mobility models , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[8]  J. Werb,et al.  Designing a positioning system for finding things and people indoors , 1998 .

[9]  Koen Langendoen,et al.  Distributed localization in wireless sensor networks: a quantitative compariso , 2003, Comput. Networks.

[10]  Li-Hsing Yen,et al.  Link probability, network coverage, and related properties of wireless ad hoc networks , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

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

[12]  Chong Wang,et al.  Novel self-configurable positioning technique for multihop wireless networks , 2005, IEEE/ACM Transactions on Networking.

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

[14]  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).

[15]  Stephen B. Wicker,et al.  On the behavior of communication links of a node in a multi-hop mobile environment , 2004, MobiHoc '04.

[16]  B. R. Badrinath,et al.  Position and orientation in ad hoc networks , 2004, Ad Hoc Networks.

[17]  Kaveh Pahlavan,et al.  Modeling of the TOA-based distance measurement error using UWB indoor radio measurements , 2006, IEEE Communications Letters.

[18]  Christian Bettstetter,et al.  On the minimum node degree and connectivity of a wireless multihop network , 2002, MobiHoc '02.

[19]  Ahmed Helmy,et al.  The IMPORTANT framework for analyzing the Impact of Mobility on Performance Of RouTing protocols for Adhoc NeTworks , 2003, Ad Hoc Networks.

[20]  Thomas Kunz,et al.  Increasing packet delivery ratio in DSR by link prediction , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[21]  Marilynn P. Wylie-Green,et al.  Robust range estimation in the presence of the non-line-of-sight error , 2001, IEEE 54th Vehicular Technology Conference. VTC Fall 2001. Proceedings (Cat. No.01CH37211).

[22]  J. Little A Proof for the Queuing Formula: L = λW , 1961 .

[23]  A. Sampath,et al.  Estimation of maximum Doppler frequency for handoff decisions , 1993, IEEE 43rd Vehicular Technology Conference.

[24]  Scott Miller,et al.  Sensitivity of wireless network simulations to a two-state Markov model channel approximation , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[25]  Shantidev Mohanty,et al.  VEPSD: a novel velocity estimation algorithm for next-generation wireless systems , 2005, IEEE Transactions on Wireless Communications.