Joint blind channel estimation and interference suppression for OFDM systems

The paper presents blind joint channel estimation and interference suppression for orthogonal frequency-division multiplexing (OFDM) systems. Our approach uses a generalized multichannel minimum variance principle to design an equalizing filterbank that preserves the desired signal components and suppresses the overall interference. The channel estimate is then obtained by deriving an asymptotically tight lower bound of the filterbank output power, which reduces the problem to a quadratic minimization. While a channel estimate may be obtained by directly maximizing the filterbank output power through multidimensional nonlinear searches, such an approach is computationally prohibitive and suffers local convergence. Numerical examples show that the proposed scheme approaches the Cramer-Rao bound (CRB) as the SNR increases. It also exhibits low sensitivity to unknown narrowband interference and compares favorably with a subspace blind channel estimator.