VP-FLMS: A Novel Variable Power Fractional LMS Algorithm

Shujaat Khan; Muhammad Usman; Imran Naseem; Roberto Togneri; Mohammed Bennamoun

doi:10.1109/ICUFN.2017.7993796

VP-FLMS: A Novel Variable Power Fractional LMS Algorithm

Shujaat Khan, Muhammad Usman, Imran Naseem, Roberto Togneri, Mohammed Bennamoun

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

11 Citations (Scopus)

Abstract

In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm using the concept of instantaneous error energy. The proposed algorithm named variable power-FLMS (VP-FLMS) is computationally less expensive and dynamically adapts the fractional power of the FLMS to achieve a high convergence rate with a low steady state error. For the evaluation purpose, the problems of channel estimation and channel equalization are considered. The experiments clearly show that the proposed approach achieves better convergence rate and lower steady-state error compared to the FLMS.

Original language	English
Title of host publication	ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks
Editors	Yeong Min Jang, Gianluca Reali, C.K. Toh, Zary Segall, Takeo Fujii
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	290-295
Number of pages	6
ISBN (Electronic)	9781509047499
DOIs	https://doi.org/10.1109/ICUFN.2017.7993796
Publication status	Published - Jul 2017
Event	9th International Conference on Ubiquitous and Future Networks, ICUFN 2017 - Milan, Italy Duration: 4 Jul 2017 → 7 Jul 2017

Conference

Conference	9th International Conference on Ubiquitous and Future Networks, ICUFN 2017
Country/Territory	Italy
City	Milan
Period	4/07/17 → 7/07/17

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10.1109/ICUFN.2017.7993796

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Khan, S., Usman, M., Naseem, I., Togneri, R., & Bennamoun, M. (2017). VP-FLMS: A Novel Variable Power Fractional LMS Algorithm. In Y. M. Jang, G. Reali, C. K. Toh, Z. Segall, & T. Fujii (Eds.), ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks (pp. 290-295). Article 7993796 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICUFN.2017.7993796

@inproceedings{1db8a25f7ab84bd091f677cf88ac111b,

title = "VP-FLMS: A Novel Variable Power Fractional LMS Algorithm",

abstract = "In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm using the concept of instantaneous error energy. The proposed algorithm named variable power-FLMS (VP-FLMS) is computationally less expensive and dynamically adapts the fractional power of the FLMS to achieve a high convergence rate with a low steady state error. For the evaluation purpose, the problems of channel estimation and channel equalization are considered. The experiments clearly show that the proposed approach achieves better convergence rate and lower steady-state error compared to the FLMS.",

keywords = "Channel equalization, Channel estimation, Fractional calculus, Least mean square (LMS), Variable step size (VSS)",

author = "Shujaat Khan and Muhammad Usman and Imran Naseem and Roberto Togneri and Mohammed Bennamoun",

year = "2017",

month = jul,

doi = "10.1109/ICUFN.2017.7993796",

language = "English",

pages = "290--295",

editor = "Jang, {Yeong Min } and Reali, {Gianluca } and Toh, {C.K. } and Segall, {Zary } and Fujii, {Takeo }",

booktitle = "ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "9th International Conference on Ubiquitous and Future Networks, ICUFN 2017 ; Conference date: 04-07-2017 Through 07-07-2017",

}

Khan, S, Usman, M, Naseem, I , Togneri, R & Bennamoun, M 2017, VP-FLMS: A Novel Variable Power Fractional LMS Algorithm. in YM Jang, G Reali, CK Toh, Z Segall & T Fujii (eds), ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks., 7993796, IEEE, Institute of Electrical and Electronics Engineers, pp. 290-295, 9th International Conference on Ubiquitous and Future Networks, ICUFN 2017, Milan, Italy, 4/07/17. https://doi.org/10.1109/ICUFN.2017.7993796

VP-FLMS: A Novel Variable Power Fractional LMS Algorithm. / Khan, Shujaat; Usman, Muhammad; Naseem, Imran et al.
ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks. ed. / Yeong Min Jang; Gianluca Reali; C.K. Toh; Zary Segall; Takeo Fujii. IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 290-295 7993796.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - VP-FLMS

T2 - 9th International Conference on Ubiquitous and Future Networks, ICUFN 2017

AU - Khan, Shujaat

AU - Usman, Muhammad

AU - Naseem, Imran

AU - Togneri, Roberto

AU - Bennamoun, Mohammed

PY - 2017/7

Y1 - 2017/7

N2 - In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm using the concept of instantaneous error energy. The proposed algorithm named variable power-FLMS (VP-FLMS) is computationally less expensive and dynamically adapts the fractional power of the FLMS to achieve a high convergence rate with a low steady state error. For the evaluation purpose, the problems of channel estimation and channel equalization are considered. The experiments clearly show that the proposed approach achieves better convergence rate and lower steady-state error compared to the FLMS.

AB - In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm using the concept of instantaneous error energy. The proposed algorithm named variable power-FLMS (VP-FLMS) is computationally less expensive and dynamically adapts the fractional power of the FLMS to achieve a high convergence rate with a low steady state error. For the evaluation purpose, the problems of channel estimation and channel equalization are considered. The experiments clearly show that the proposed approach achieves better convergence rate and lower steady-state error compared to the FLMS.

KW - Channel equalization

KW - Channel estimation

KW - Fractional calculus

KW - Least mean square (LMS)

KW - Variable step size (VSS)

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UR - http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7985824

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DO - 10.1109/ICUFN.2017.7993796

M3 - Conference paper

AN - SCOPUS:85028090233

SP - 290

EP - 295

BT - ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks

A2 - Jang, Yeong Min

A2 - Reali, Gianluca

A2 - Toh, C.K.

A2 - Segall, Zary

A2 - Fujii, Takeo

PB - IEEE, Institute of Electrical and Electronics Engineers

Y2 - 4 July 2017 through 7 July 2017

ER -

VP-FLMS: A Novel Variable Power Fractional LMS Algorithm

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