Algorithms for blind equalization with multiple antennas based on frequency domain subspaces

This paper considers the problem of recovering an unknown signal transmitted over an unknown (but stationary) multipath channel, and received by a narrowband array with unknown calibration. Unlike previously proposed multichannel blind equalization techniques, the methods described herein employ a model based on physical channel parameters rather than unstructured multiple output FIR filters. The algorithms exploit the structure of the signal and noise subspaces of the array output data when transformed to the frequency domain. Two approaches are presented. The first is an ESPRIT-like solution that provides a closed-form, but suboptimal, blind signal estimate. The second is based on maximum likelihood and, though requiring a search, is easily initialized with the ESPRIT solution. A mathematical development of the two algorithms is given, and their advantages and disadvantages relative to other currently available techniques are discussed