A novel structured channel estimation method for sparse channels with applications to multi-antenna digital TV receivers

Abstract

We introduce a novel channel impulse response (CIR) estimation method, for sparse multipath channels, with applications to digital TV receivers with multiple antennas. Our method uses symbol rate samples of the receiver matched filter output, and it is based on blending the least squares based channel estimation and the correlation based channel estimation methods. We first overview the shortcomings of the least squares and the correlation based channel estimation algorithms, where a training sequence is utilized in both cases. The performance of the new channel estimation method is demonstrated, such that the channel estimation becomes more robust, and the overall quality of the estimate improves by recovering the pulse shape which is naturally embedded in the overall channel impulse response. We demonstrate how both methods can be combined effectively to minimize the problems associated with the effective channel delay spread being longer than the known training sequence can support. Examples are drawn from the ATSC digital TV 8-VSB system (see ATSC Digital Television Standard, A/53, 1995) with a multi-antenna receiver. The delay spread for digital TV systems can be as long as several hundred times the symbol duration; however, digital TV channels are, in general, sparse where there are only a few dominant multipaths. Finally, we derive the noise variance estimator.