Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach

Muhammad Sadiq Sohail; Tareq Y. Al-Naffouri; Samir N. Al-Ghadhban

doi:10.1109/SPAWC.2012.6292950

Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach

Muhammad Sadiq Sohail, Tareq Y. Al-Naffouri, Samir N. Al-Ghadhban

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

14 Scopus citations

Abstract

This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that the NBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paper also presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations. © 2012 IEEE.

Original language	English (US)
Title of host publication	2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	45-49
Number of pages	5
ISBN (Print)	9781467309714
DOIs	https://doi.org/10.1109/SPAWC.2012.6292950
State	Published - Jun 2012

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KAUST Repository Item: Exported on 2020-10-01

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Sohail, M. S., Al-Naffouri, T. Y., & Al-Ghadhban, S. N. (2012). Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach. In 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (pp. 45-49). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SPAWC.2012.6292950

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abstract = "This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that the NBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paper also presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations. {\textcopyright} 2012 IEEE.",

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Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach. / Sohail, Muhammad Sadiq; Al-Naffouri, Tareq Y.; Al-Ghadhban, Samir N.
2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Institute of Electrical and Electronics Engineers (IEEE), 2012. p. 45-49.

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

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AU - Al-Naffouri, Tareq Y.

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N1 - KAUST Repository Item: Exported on 2020-10-01

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AB - This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that the NBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paper also presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations. © 2012 IEEE.

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BT - 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach

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