A low-complexity ML channel estimator for OFDM

Abstract—Orthogonal frequency-division multiplexing with cyclic prefix enables low-cost frequency-domain mitigation of multipath distortion. However, to determine the equalizer coeffi-cients, knowledge of the channel frequency response is required. While a straightforward approach is to measure the response to a known pilot symbol sequence, existing literature reports a significant performance gain when exploiting the frequency correlation properties of the channel. Expressing this correlation by the finite delay spread, we build a deterministic model param-etrized by the channel impulse response and, based on this model, derive the maximum-likelihood channel estimator. In addition to being optimal (up to the modeling error), this estimator receives an elegant time–frequency interpretation. As a result, it has a significantly lower complexity than previously published methods. Index Terms—Equalizers, orthogonal frequency-division multi-plexing (OFDM). I