Cyclic prefix assisted sparse channel estimation for OFDM systems

In this paper an efficient algorithm is presented for the estimation of a channel modelled as sparse for an OFDM system. Conventional Pilot-Based techniques and blind estimation techniques require a large number of pilot tones and complex mathematical computations respectively to estimate the channel vector. This drawback is particularly pronounced in sparse systems where the effective channel vector has a very few number of taps. The proposed method uses a modification made to the Cyclic Prefix to detect the position of the most significant taps (MST) for a sparse channel. Least Square estimation method is then used to effectively estimate the channel vector. Prior knowledge of the most significant tap positions obtained from the cyclic prefix ensures spectral and computational efficiencies.