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Efficient Interpolation Method for Wireless Communications and Signal Processing Applications

Interpolation involves the process of estimating values at positions in between the adjacent samples, which has very fundamental and applied implications in signal processing and communication systems. In this work, a new method of cubic spline interpolation (CSI) is proposed and derived mathematically from the input samples respecting the time-domain boundary conditions, and the corresponding piecewise polynomials are optimized in the frequency domain to achieve good spectral properties. A comparative analysis of several prior arts, including arbitrary frequency response polynomial (AFRP) and basis spline (B-spline) is also presented, giving a clear overview of the advantages associated with the proposed technique in terms of implementation complexity, latency, and in-band and out-of-band spectral performance. The measurement results with three different radio frequency (RF) power amplifier (PA) prototypes using an input stimulus comprised of different instantaneous bandwidth (iBW) carrier aggregated 5G new radio (NR) waveform are demonstrated to highlight the improved performance in the context of digital predistortion (DPD) correction. Finally, the architecture of the proposed method is illustrated, which is suitable for real-time high-speed digital implementation.