Low-complexity channel estimator based on windowed DFT and scalar Wiener filter for OFDM system

The paper presents a low complexity channel estimator based on windowed discrete Fourier transform (DFT) and scalar Wiener filter for orthogonal frequency division multiplexing (OFDM) mobile communications systems. In the method, a generalized Hanning window is applied to the channel frequency response observation vector in the frequency domain to reduce the spectral leakage, and a scalar Wiener filter is applied to the effective channel impulse response in the time domain to suppress the channel noise. Analysis results show that the proposed method's performance is close to the optimal minimum mean square error (MMSE) estimator and is much better than the direct DFT based estimator. Compared with the optimal MMSE estimator, however, the computation load of the proposed method can be significantly reduced because the IDFT/DFT transforms can be implemented with the fast algorithms IFFT/FFT.