Frequency-domain filtering is effective both for realizing asymptotically orthogonalized designs which can rapidly acquire a signal with a large eigenvalue spread and for realizing efficient block implementations. However, most previous work in this area has assumed a stationary input signal. The authors further define the extensions necessary to accommodate the cyclostationary signal seen by a fractionally spaced equalizer. When the cyclostationary nature of the signal is exploited, the asymptotically exact Wiener solution can be realized by two equivalent architectures. The first architecture results from demultiplexing the input data into parallel, decimated, stationary signals which are individually transformed. Postprocessing then coherently combines corresponding frequency bins. The second, equivalent, architecture results from direct transformation of the input cyclostationary signal. Postprocessing coherently combines frequency bins, which exhibit spectral correlation. Special periodic noise spectra are identified which expedite collapsing to half the number of spectral bins.
展开▼
