Abstract
Higher sampling rates are essential in any communication system at present due to the demand for higher data rates. Such high sampling rates can be achieved with time-interleaved analog-to-digital converters (TI-ADCs). Even though TI-ADCs are faster, the sampling time offset is a setback. The sampling time offsets present in ADCs generate nonuniform samples. In the reconstruction process, these nonuniform samples might produce an erroneous signal. In this work, estimation of these sampling time offsets is performed using differential evolution algorithm. The proposed algorithm efficiently detects the sampling time offsets with minimum number of iterations. The estimated sampling time offsets are used to reconstruct the signal using fractional delay filters. Performance of the proposed algorithm is tested by considering various signals, i.e., speech signal, sinusoidal, and amplitude modulated signal (AM). Signal-to-noise ratio (SNR) and signal-to-noise distortion ratio (SNDR) are calculated for the signals. The results are compared with the existing works and noteworthy improvement with the proposed algorithm is demonstrated.
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Chakravarthi, M.V.N., Chandramohan, B. (2019). Estimation of Sampling Time Offsets in an N-Channel Time-Interleaved ADC Network Using Differential Evolution Algorithm and Correction Using Fractional Delay Filters. In: Tanveer, M., Pachori, R. (eds) Machine Intelligence and Signal Analysis. Advances in Intelligent Systems and Computing, vol 748. Springer, Singapore. https://doi.org/10.1007/978-981-13-0923-6_23
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DOI: https://doi.org/10.1007/978-981-13-0923-6_23
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