Noise plus interference power estimation in adaptive OFDM systems

Noise variance and signal-to-noise ratio (SNR) 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 affects the OFDM spectrum unevenly. This paper proposes an adaptive windowing technique to estimate the noise power that takes into account the variation of the noise statistics across the OFDM sub-carrier index as well as across OFDM symbols. The proposed method provides many local estimates, allowing tracking of the variation of the noise statistics in frequency and time. A mean-squared-error (MSE) expression in order to choose the optimal window dimensions for averaging in time and frequency is derived. Evaluation of the performance with computer simulations show that the proposed method tracks the local statistics of the noise more efficiently than conventional methods.