Kalman-based time-varying sparse channel estimation

Jin Hyeok Yoo, Ali Irtaza Sayed, Jun Won Choi, Byonghyo Shim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we investigate a problem of estimating time-varying sparse channel impulse response for wireless communications. We are primarily interested in the scenario where the support of channels (i.e., the location of nonzero elements in channel impulse response) rarely changes within a local period of time. The proposed channel estimator estimates both support and amplitudes of the channel impulse response in an iterative fashion using the expectation and maximization algorithm. In order to exploit the (temporal) joint sparsity as well as temporal correlation of the channel gains, the proposed channel estimator performs two steps 1) E-step: Kalman smoothing of channel gains under the sparsity constraint and 2) M-step: semidefinite relaxation (SDR) technique for estimating the common support of channel impulse responses. Numerical evaluation shows that the proposed method performs close to the Oracle-based Kalman smoother and outperforms the existing sparse channel estimators.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Communication Systems, ICCS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509034239
DOIs
Publication statusPublished - 2017 Jan 25
Externally publishedYes
Event2016 IEEE International Conference on Communication Systems, ICCS 2016 - Shenzhen, China
Duration: 2016 Dec 142016 Dec 16

Other

Other2016 IEEE International Conference on Communication Systems, ICCS 2016
CountryChina
CityShenzhen
Period16/12/1416/12/16

Fingerprint

Channel estimation
Impulse response
Communication

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Yoo, J. H., Sayed, A. I., Choi, J. W., & Shim, B. (2017). Kalman-based time-varying sparse channel estimation. In 2016 IEEE International Conference on Communication Systems, ICCS 2016 [7833599] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCS.2016.7833599

Kalman-based time-varying sparse channel estimation. / Yoo, Jin Hyeok; Sayed, Ali Irtaza; Choi, Jun Won; Shim, Byonghyo.

2016 IEEE International Conference on Communication Systems, ICCS 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7833599.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yoo, JH, Sayed, AI, Choi, JW & Shim, B 2017, Kalman-based time-varying sparse channel estimation. in 2016 IEEE International Conference on Communication Systems, ICCS 2016., 7833599, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on Communication Systems, ICCS 2016, Shenzhen, China, 16/12/14. https://doi.org/10.1109/ICCS.2016.7833599
Yoo JH, Sayed AI, Choi JW, Shim B. Kalman-based time-varying sparse channel estimation. In 2016 IEEE International Conference on Communication Systems, ICCS 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7833599 https://doi.org/10.1109/ICCS.2016.7833599
Yoo, Jin Hyeok ; Sayed, Ali Irtaza ; Choi, Jun Won ; Shim, Byonghyo. / Kalman-based time-varying sparse channel estimation. 2016 IEEE International Conference on Communication Systems, ICCS 2016. Institute of Electrical and Electronics Engineers Inc., 2017.
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