Papoulis-Gerchberg Hybrid Filter Bank Receiver for Cognitive-/Software-Defined Radio Systems

摘要

Emerging Software-Defined Radios (SDRs) should be prepared to deal with wide-band sparse-spectrum RF signals. This requires the availability of advanced analog-to-digital front-ends with a fast sampling rate, large dynamic range and capable of handling high peak-to-average-power-ratio (PAPR) signals. A Hybrid Filter Bank (HFB) receiver solution was recently proposed by the authors to address such demanding requirements in the SDR context, with special emphasis on the RF analog part. In this paper, as further research, a maximally-decimated five-channel HFB for its intermediate-frequency (IF) part is shown. Unlike its previously reported RF counterpart, it makes use of the Papoulis-Gerchberg algorithm to attain a more efficient implementation in terms of computational cost and reconfigurability. For this HFB-based IF SDR receiver, the digital filters compensating the analog design imperfections are evaluated and real-time signal-reconstruction tests for wide-band and narrow-band signals are carried out. A sensitivity discussion is also provided.