An improved two-way training for discriminatory channel estimation via semiblind approach

Junjie Yang, Rong Yu*, Xiangyun Zhou, Yan Zhang

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    This paper studies the discriminatory channel estimation (DCE) performance between a legitimate receiver (LR) and an unauthorized receiver (UR) in the multiple-input multiple-output (MIMO) wireless systems. DCE is a recently developed concept that intentionally degrades the channel estimation at the UR so as to minimize the probability of confidential information being eavesdropped by the UR. Usually, the existing DCE scheme is based on the linear minimum mean square error (LMMSE) method with two-way training. In this paper, we propose a new two-way training for DCE based on semiblind approach, e.g., the whitening-rotation (WR)-based channel estimator. To characterize the DCE performance, we derive the closed-form of the normalized mean squared error (NMSE) to the channel estimation at both the LR and the UR. Simulation results show that the proposed two-way training achieves higher performance compared to the two-way training designs in the literature.

    Original languageEnglish
    Title of host publication2014 IEEE International Conference on Communications, ICC 2014
    PublisherIEEE Computer Society
    Pages4442-4447
    Number of pages6
    ISBN (Print)9781479920037
    DOIs
    Publication statusPublished - 2014
    Event2014 1st IEEE International Conference on Communications, ICC 2014 - Sydney, NSW, Australia
    Duration: 10 Jun 201414 Jun 2014

    Publication series

    Name2014 IEEE International Conference on Communications, ICC 2014

    Conference

    Conference2014 1st IEEE International Conference on Communications, ICC 2014
    Country/TerritoryAustralia
    CitySydney, NSW
    Period10/06/1414/06/14

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