Method and apparatus for calibrating data-dependent noise prediction
AssigneeInfineon Technologies AG
InventorsJonathan J. Ashley, Heinrich J. Stockmanns
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AssigneeInfineon Technologies AG
InventorsJonathan J. Ashley, Heinrich J. Stockmanns
Estimating the term…
Disclosed herein is an apparatus and method of calibrating the parameters of a Viterbi detector 138 in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. An offline algorithm for calculating the parameters of data-dependent noise predictive filters 304A-D is presented which has two phases: a noise statistics estimation or training phase, and a filter calculation phase. During the training phase, products of pairs of noise samples are accumulated in order to estimate the noise correlations. Further, the results of the training phase are used to estimate how wide (in bits) the noise correlation accumulation registers need to be. The taps [t2[k], t1[k], t0[k]] of each FIR filter are calculated based on estimates of the entries of a 3-by-3 conditional noise correlation matrix C[k] defined by Cij[k]=E(ni−3nj−3|NRZ condition k).
A method of calibrating a Viterbi detector, said Viterbi detector comprising at least one noise predictive filter, said method comprising:
An apparatus for calibrating a Viterbi detector comprising at least one noise predictive filter, said apparatus comprising:
An apparatus for calibrating a Viterbi detector, said Viterbi detector comprising at least one noise predictive filter, said apparatus comprising:
Dependencies are inferred from the claim text.