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To jointly track frequency drift (or fine frequency offset) and channel state variation for orthogonal frequency division multiplexing (OFDM) communications over mobile wireless channels, the maximum-likelihood (ML) estimation techniques are commonly adopted. A major difficulty arises from the highly nonlinear nature of the log-likelihood function which renders local extrema or multiple solutions...
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...
We present exact symbol error rate (SER) performance analysis for M-QAM OFDM systems over Ricean and Rayleigh fading is analyzed. Both slow and fast quasi-static fading as well as frequency-selective and -nonselective channels are considered.
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