淡江大學機構典藏:Item 987654321/61008
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/61008


    Title: Effective Adaptive Iteration Algorithm for Frequency Tracking and Channel Estimation in OFDM Systems
    Authors: Liu, Hong-Yu;Yen, R.Y.
    Contributors: 淡江大學電機工程學系
    Date: 2010-05
    Issue Date: 2011-10-15 01:14:10 (UTC+8)
    Publisher: Piscataway: Institute of Electrical and Electronics Engineers
    Abstract: For joint maximum-likelihood (ML) frequency tracking and channel estimation using orthogonal frequency-division multiplexing (OFDM) training blocks in OFDM communications over mobile wireless channels, a major difficulty is the local extrema or multiple-solution complication arising from the multidimensional log-likelihood function. To overcome this, we first obtain crude ML frequency-offset estimators using single-time-slot samples from the received time-domain OFDM block. These crude frequency estimators are shown to have unique closed-form solutions. We then optimally combine these crude frequency estimators in the linear-minimum-mean-square-error (LMMSE) sense for a more accurate solution. Finally, by alternatively updating the LMMSE frequency estimator and the ML channel estimator through adaptive iterations, we successfully avoid the use of a multidimensional log-likelihood function, hence obviating the complex task of global solution search and, meanwhile, achieve good estimation performance. Our estimators have mean square errors (MSEs) tightly close to Cramer-Rao bounds (CRBs) with a wide tracking range.
    Relation: IEEE Transactions on Vehicular Technology 59(4), pp.2093-2097
    DOI: 10.1109/TVT.2010.2042738
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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