Blind multichannel adaptive MMSE equalization with controlled delay
SSAP '96 Proceedings of the 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing (SSAP '96)
IEEE Transactions on Signal Processing
A least-squares approach to blind channel identification
IEEE Transactions on Signal Processing
Subspace methods for the blind identification of multichannel FIRfilters
IEEE Transactions on Signal Processing
Blind fractionally spaced equalization of noisy FIR channels: direct and adaptive solutions
IEEE Transactions on Signal Processing
Direct blind MMSE channel equalization based on second-orderstatistics
IEEE Transactions on Signal Processing
Fast maximum likelihood for blind identification of multiple FIRchannels
IEEE Transactions on Signal Processing
Closed-form blind symbol estimation in digital communications
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Direct blind equalizers of multiple FIR channels: a deterministicapproach
IEEE Transactions on Signal Processing
Blind channel approximation: effective channel order determination
IEEE Transactions on Signal Processing
Blind equalization using least-squares lattice prediction
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Constrained optimization methods for direct blind equalization
IEEE Journal on Selected Areas in Communications
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This paper presents a new direct blind channel equalizer by using spatial adaptive filtering technique. Two correlation matrices with time delay parameters d and d + 1 are incorporated into design to guarantee the extraction of a d-delay signal. To reduce the system computation complexity of the algorithm, a projection minimization criterion is introduced. It is shown that the optimal equalizer weights can be found by searching the least dominant eigenvector of a generalized eigenvalue problem. The proposed algorithm has benefits of extracting the signals with delay not restricted to the first or the last of a received data. This paper also develops an optimal delay determination method for selecting the delay to reach the best performance. Several simulation examples demonstrate that the proposed algorithm has fast convergence speed and is robust to the channel order selection.