Efficient Reconstruction of Two-Periodic Nonuniformly Sampled Signals Applicable to Time-Interleaved ADCs

Abstract: Nonuniform sampling occurs in many practical applications either intentionally or unintentionally. This thesis deals with the reconstruction of two-periodic nonuniform signals which is of great importance in two-channel time-interleaved analog-to-digital converters. In a two-channel time-interleaved ADC, aperture delay mismatch between the channels gives rise to a two-periodic nonuniform sampling pattern, resulting in distortion and severely affecting the linearity of the converter. The problem is solved by digitally recovering a uniformly sampled sequence from a two-periodic nonuniformly sampled set. For this purpose, a time-varying FIR filter is employed. If the sampling pattern is known and fixed, this filter can be designed in an optimal way using least-squares or minimax design. When the sampling pattern changes now and then as during the normal operation of time-interleaved ADC, these filters have to be redesigned. This has implications on the implementation cost as general on-line design is cumbersome. To overcome this problem, a novel time-varying FIR filter with polynomial impulse response is developed and characterized in this thesis. The main advantage with these filters is that on-line design is no longer needed. It now suffices to perform only one design before implementation and in the implementation it is enough to adjust only one variable parameter when the sampling pattern changes. Thus the high implementation cost is decreased substantially. Filter design and the associated performance metrics have been validated using MATLAB. The design space has been explored to limits imposed by machine precision on matrix inversions. Studies related to finite wordlength effects in practical filter realisations have also been carried out. These formulations can also be extended to the general M - periodic nonuniform sampling case.