SFT-based Channel Estimation for OFDM Communication Systems

Channel estimation plays an important role in OFDM, which is favored for broadband systems. Conventional channel estimation methods transform domain by DFT to suppress the time domain noise of the LS estimates. Sparse Fourier Transform (SFT) has been proposed as a solution to shorten the computational complexity of the Fourier transform of sparse signal. In this paper, we propose an enhanced algorithm to make a better trade-off between performance and complexity. The dominant entries of channel impulse response are obtained directly by sparse inverse Fourier transform. Simulation results demonstrate that the proposed algorithm yields a satisfactory estimation performance at a lower computational complexity.