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Noise variance and signal-to-noise ratio are important parameters for adaptive orthogonal frequency-division multiplexing (OFDM) systems since they serve as a standard measure of signal quality. Conventional algorithms assume that the noise statistics remain constant over the OFDM frequency band and, thereby, average the instantaneous noise samples to get a single estimate. In reality, noise is often made up of white Gaussian noise, along with correlated colored noise that unevenly affects the OFDM spectrum. This paper proposes a minimum mean square error (MMSE) filtering technique to estimate the noise power that takes into account the variation of the noise statistics across the OFDM subcarrier index, as well as across OFDM symbols. The proposed method provides many local estimates that allow tracking of the variation of noise statistics in frequency and time. The MMSE filter coefficients are obtained from the mean-squared-error expression, which can be calculated using the noise statistics. Evaluation of the performance with computer simulations shows that the proposed method tracks the local statistics of the noise more efficiently than conventional methods.