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 paperConference paper

    7 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 languageEnglish
    Title of host publicationICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks
    EditorsYeong Min Jang, Gianluca Reali, C.K. Toh, Zary Segall, Takeo Fujii
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages290-295
    Number of pages6
    ISBN (Electronic)9781509047499
    DOIs
    Publication statusPublished - Jul 2017
    Event9th International Conference on Ubiquitous and Future Networks, ICUFN 2017 - Milan, Italy
    Duration: 4 Jul 20177 Jul 2017

    Conference

    Conference9th International Conference on Ubiquitous and Future Networks, ICUFN 2017
    CountryItaly
    CityMilan
    Period4/07/177/07/17

    Fingerprint

    Channel estimation
    Experiments

    Cite this

    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). [7993796] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICUFN.2017.7993796
    Khan, Shujaat ; Usman, Muhammad ; Naseem, Imran ; Togneri, Roberto ; Bennamoun, Mohammed. / VP-FLMS : A Novel Variable Power Fractional LMS Algorithm. ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks. editor / Yeong Min Jang ; Gianluca Reali ; C.K. Toh ; Zary Segall ; Takeo Fujii. IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 290-295
    @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 = "7",
    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",

    }

    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; Togneri, Roberto; Bennamoun, Mohammed.

    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 paperConference paper

    TY - GEN

    T1 - VP-FLMS

    T2 - A Novel Variable Power Fractional LMS Algorithm

    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)

    UR - http://www.scopus.com/inward/record.url?scp=85028090233&partnerID=8YFLogxK

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

    U2 - 10.1109/ICUFN.2017.7993796

    DO - 10.1109/ICUFN.2017.7993796

    M3 - Conference paper

    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

    ER -

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