Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm

Xiao Ma; Mohammed M. Olama; Seddik M. Djouadi; Charalambos D. Charalambous

doi:10.1109/RWS.2011.5725492

Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm

Xiao Ma, Mohammed M. Olama, Seddik M. Djouadi, Charalambos D. Charalambous

Computational Systems Engineering and Cy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In this paper, we are concerned with the estimation and identification of time-varying wireless longterm fading channels. The dynamics of the fading channels are captured using a mean-reverting linear stochastic differential equation driven by a Brownian motion. Recursive estimation and identification algorithms solely from received signal strength data are developed. These algorithms are based on combining the particle filter (PF) with the expectation maximization (EM) algorithm that estimate and identify the power path-loss of the channel and its parameters, respectively. Numerical results are provided to evaluate the accuracy of the proposed algorithms.

Original language	English
Title of host publication	2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011
Pages	13-16
Number of pages	4
DOIs	https://doi.org/10.1109/RWS.2011.5725492
State	Published - 2011
Event	2011 IEEE Radio and Wireless Symposium, RWS 2011 - Phoenix, AZ, United States Duration: Jan 16 2011 → Jan 19 2011

Publication series

Name	2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011

Conference

Conference	2011 IEEE Radio and Wireless Symposium, RWS 2011
Country/Territory	United States
City	Phoenix, AZ
Period	01/16/11 → 01/19/11

Keywords

EM algorithm
Long-term fading
Particle filter

Access to Document

10.1109/RWS.2011.5725492

Cite this

Ma, X., Olama, M. M., Djouadi, S. M., & Charalambous, C. D. (2011). Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm. In 2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011 (pp. 13-16). Article 5725492 (2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011). https://doi.org/10.1109/RWS.2011.5725492

Ma, Xiao ; Olama, Mohammed M. ; Djouadi, Seddik M. et al. / Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm. 2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011. 2011. pp. 13-16 (2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011).

@inproceedings{3a5b62a903974907b3233a606eab0ef5,

title = "Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm",

abstract = "In this paper, we are concerned with the estimation and identification of time-varying wireless longterm fading channels. The dynamics of the fading channels are captured using a mean-reverting linear stochastic differential equation driven by a Brownian motion. Recursive estimation and identification algorithms solely from received signal strength data are developed. These algorithms are based on combining the particle filter (PF) with the expectation maximization (EM) algorithm that estimate and identify the power path-loss of the channel and its parameters, respectively. Numerical results are provided to evaluate the accuracy of the proposed algorithms.",

keywords = "EM algorithm, Long-term fading, Particle filter",

author = "Xiao Ma and Olama, {Mohammed M.} and Djouadi, {Seddik M.} and Charalambous, {Charalambos D.}",

year = "2011",

doi = "10.1109/RWS.2011.5725492",

language = "English",

isbn = "9781424476855",

series = "2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011",

pages = "13--16",

booktitle = "2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011",

note = "2011 IEEE Radio and Wireless Symposium, RWS 2011 ; Conference date: 16-01-2011 Through 19-01-2011",

}

Ma, X, Olama, MM, Djouadi, SM & Charalambous, CD 2011, Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm. in 2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011., 5725492, 2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011, pp. 13-16, 2011 IEEE Radio and Wireless Symposium, RWS 2011, Phoenix, AZ, United States, 01/16/11. https://doi.org/10.1109/RWS.2011.5725492

Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm. / Ma, Xiao; Olama, Mohammed M.; Djouadi, Seddik M. et al.
2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011. 2011. p. 13-16 5725492 (2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper, we are concerned with the estimation and identification of time-varying wireless longterm fading channels. The dynamics of the fading channels are captured using a mean-reverting linear stochastic differential equation driven by a Brownian motion. Recursive estimation and identification algorithms solely from received signal strength data are developed. These algorithms are based on combining the particle filter (PF) with the expectation maximization (EM) algorithm that estimate and identify the power path-loss of the channel and its parameters, respectively. Numerical results are provided to evaluate the accuracy of the proposed algorithms.

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Ma X, Olama MM, Djouadi SM, Charalambous CD. Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm. In 2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011. 2011. p. 13-16. 5725492. (2011 IEEE Radio and Wireless Week, RWW 2011 - 2011 IEEE Radio and Wireless Symposium, RWS 2011). doi: 10.1109/RWS.2011.5725492

Estimation and identification of time-varying long-term fading channels via the particle filter and the em algorithm

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