Data - Recursive Algorithms for Blind Channel Identi cation inDirect - Sequence
نویسندگان
چکیده
Algorithms for performing blind channel identiication for a binary phase-shift keyed (BPSK) direct-sequence spread-spectrum (DS/SS) system operating over a fading channel are presented. These algorithms are derived by identifying the DS/SS system as a discrete oversampled system with intersymbol interference. In this setting the spreading code can be viewed as a transmit lter, the knowledge of which can be used to aid in channel identii-cation. An oo-line solution to the channel identiication problem involves the determination of the eigenvector corresponding to the minimum eigenvalue of a matrix that depends on the correlation statistics of the samples of the received signal. In this paper, the online solution is derived for the case that the transmit lter and propagation channel are unknown and jointly identiied. Novel low complexity stochastic gradient algorithms and conjugate gradient algorithms are derived and mean convergence conditions given. Then it is shown how the knowledge of the spreading code can be incorporated to aid in identiication. An algorithm is then derived that utilizes trellis searching for joint data and channel identiica-tion for oversampled systems. Finally, numerical results in the form of channel estimation error are presented.
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