A risk minimization framework for channel estimation in OFDM systems

Karthik Upadhya*, Chandra Sekhar Seelamantula, K. V S Hari

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    5 Citations (Scopus)


    We address the problem of channel estimation for cyclic-prefix (CP) Orthogonal Frequency Division Multiplexing (OFDM) systems. We focus on situations wherein knowledge of channel statistics are not available a priori, and model the channel as a vector of unknown deterministic parameters. Since computing the mean-square error (MSE) is not practicable in such a scenario, we propose a novel technique using Stein's lemma to obtain an unbiased estimate of the mean-square error, namely Stein's unbiased risk estimate (SURE). The channel estimate is obtained from noisy observations using linear and nonlinear denoising functions, whose parameters are chosen to minimize SURE. Based on computer simulations, it is shown that using SURE-based channel estimates for equalization offers an improvement in signal-to-noise performance over existing channel estimation schemes.

    Original languageEnglish
    Pages (from-to)78-87
    Number of pages10
    JournalSignal Processing
    Publication statusPublished - 1 Nov 2016
    MoE publication typeA1 Journal article-refereed


    • Channel estimation
    • Stein's lemma
    • Stein's unbiased risk estimate


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