Recursive Estimation and Identification of Wireless Ad Hoc Channels from Measurements

Mohammed Olama; Yanyan Li; Seddik Djouadi; Travis Goodspeed; T. Kuruganti

2nd International ICST Workshop on Performance Control in Wireless Sensor Networks

Research Article

Recursive Estimation and Identification of Wireless Ad Hoc Channels from Measurements

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Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/pwsn.2007.2264,
    author={Mohammed Olama and Yanyan Li and Seddik Djouadi and Travis Goodspeed and T. Kuruganti},
    title={Recursive Estimation and Identification of Wireless Ad Hoc Channels from Measurements},
    proceedings={2nd International ICST Workshop on Performance Control in Wireless Sensor Networks},
    proceedings_a={PWSN},
    year={2010},
    month={5},
    keywords={Ad hoc channel expectation maximization algorithm Kalman filter stochastic state space representation.},
    doi={10.4108/pwsn.2007.2264}
}

Mohammed Olama
Yanyan Li
Seddik Djouadi
Travis Goodspeed
T. Kuruganti
Year: 2010
Recursive Estimation and Identification of Wireless Ad Hoc Channels from Measurements
PWSN
ICST
DOI: 10.4108/pwsn.2007.2264

Mohammed Olama¹^,*, Yanyan Li¹^,*, Seddik Djouadi¹^,*, Travis Goodspeed²^,*, T. Kuruganti²^,*

1: University of Tennessee 1508 Middle Drive Knoxville, TN 37919, USA Tel: 001 865 974 5447
2: Oak Ridge National Laboratory, 1 Bethel Valley Road, MS-6085 Oak Ridge, TN 37831 Tel: 001 865 241 2874

*Contact email: molama@utk.edu, yli24@utk.edu, djouadi@ece.utk.edy, goodspeedtm@ornl.gov, kurugantipv@ornl.gov

Abstract

This paper is concerned with a time varying wireless ad hoc channel modeling, its parameter estimation and system identification from received signal measurement data. The channel model is represented in state space form, while the expectation maximization algorithm and Kalman filtering are used in the channel parameter and state estimation, respectively. The proposed algorithm is recursive, and therefore the inphase and quadrature components of the ad hoc channel and its parameters are estimated online from received signal measurements. The proposed algorithm is tested using measurement data collected from moving wireless sensor nodes, and the results are presented.

Keywords: Ad hoc channel expectation maximization algorithm Kalman filter stochastic state space representation.

Published: 2010-05-16
Modified: 2011-09-18

: http://dx.doi.org/10.4108/pwsn.2007.2264