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On the use of signal subspace information in blind FIR channel estimation

In this paper, we consider the problem of blind channel estimation for single-input, single-output (SISO) system. Our main aim is to provide a new consideration in the subspace-based blind channel estimation. Instead of utilizing the noise subspace, as usually the case, we propose a new algorithm that makes use of the signal subspace signature. The new algorithm is shown to give a comparable performance with that of the noise subspace-based methods. A similar idea can be applied straightforwardly to single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) systems.