Abstract
In this letter, we propose a low-complexity sparse channel estimation method for orthogonal frequency division multiplexing (OFDM) systems. The proposed method uses a discrete Fourier transform (DFT)-based technique for channel estimation and a novel sorted noise space discrimination technique to estimate the channel length and tap positions. Simulation results demonstrate that the reduction in signal space improves the channel estimation performance.
