Fractionally spaced blind equalization using polyperiodic linear filtering
Performance of fractionally spaced equalizers using polyperiodic linear filtering is depicted. The fractionally sampled version of an arbitrary stable channel's outputs with stationary random inputs exhibit cyclostationarity with cycle frequencies being integer multiples of the reciprocal of the oversampling factor. By optimally polyperiodic linear filtering the oversampled outputs, we can fully utilize the cyclostationary property. With some traditional Bussgang techniques, such as stop-and-go decision-directed method, to adaptively update the filter coefficients, the convergence rate of the fractionally spaced equalizers proposed is improved, while the complexity retains in the same order as original Bussgang ones. Some computer simulation results are shown to demonstrate the improvement we can achieve.