Advertisement

Reconfigurable FPGA-Based Channelization Using Polyphase Filter Banks for Quantum Computing Systems

  • Johannes Pfau
  • Shalina Percy Delicia Figuli
  • Steffen Bähr
  • Jürgen Becker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10824)

Abstract

Recently proposed quantum systems use frequency multiplexed qubit technology for readout electronics rather than analog circuitry, to increase cost effectiveness of the system. In order to restore individual channels for further processing, these systems require a demultiplexing or channelization approach which can process high data rates with low latency and uses few hardware resources. In this paper, a low latency, adaptable, FPGA-based channelizer using the Polyphase Filter Bank (PFB) signal processing algorithm is presented. As only a single prototype lowpass filter needs to be designed to process all channels, PFBs can be easily adapted to different requirements and further allow for simplified filter design. Due to reutilization of the same filter for each channel they also reduce hardware resource utilization when compared to the traditional Digital Down Conversion approach. The realized system architecture is extensively generic, allowing the user to select from different numbers of channels, sample bit widths and throughput specifications. For a test setup using a 28 coefficient transpose filter and 4 output channels, the proposed architecture yields a throughput of 12.8 Gb/s with a latency of 7 clock cycles.

Keywords

Quantum computing FPGA Signal processing Channelization 

References

  1. 1.
    Lillington, J.: Comparison of wideband channelisation architectures. In: International Signal Processing Conference (ISPC), Dallas (2003)Google Scholar
  2. 2.
    Meyer, J., et al.: Ultra high speed digital down converter design for Virtex-6 FPGAs. In: 17th International OFDM Workshop 2012 (InOWo 2012), 1–5 (2012)Google Scholar
  3. 3.
    Meyer, J., et al.: A novel system on chip for software-defined, high-speed OFDM signal processing. In: 2013 26th Symposium on Integrated Circuits and Systems Design (SBCCI), 1–6 (2013)Google Scholar
  4. 4.
    Harris, F.J.: Multirate Signal Processing for Communication Systems. Prentice Hall PTR, Upper Saddle River (2004)Google Scholar
  5. 5.
    Crochiere, R.E., Rabiner, L.R.: Multirate Digital Signal Processing. Prentice-Hall, Eaglewood Cliffs (1983)Google Scholar
  6. 6.
    Harris, F.J., Dick, C., Rice, M.: Digital receivers and transmitters using polyphase filter banks for wireless communications. IEEE Trans. Microw. Theory Tech. 51, 1395–1412 (2003)CrossRefGoogle Scholar
  7. 7.
    Wang, H., Lu, Y., Wang, X.: Channelized Receiver with WOLA Filterbank. In: 2006 CIE International Conference on Radar (2006)Google Scholar
  8. 8.
    Löllmann, H.W., Vary, P.: Low delay filter-banks for speech and audio processing. In: Hänsler, E., Schmidt, G. (eds.) Speech and Audio Processing in Adverse Environments. Signals and Communication Technology, pp. 13–61. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-70602-1_2CrossRefGoogle Scholar
  9. 9.
    Tuthill, J., Hampson, G., Bunton, J.D., Harris, F.J., Brown, A., Ferris, R., Bateman, T.: Compensating for oversampling effects in polyphase channelizers: a radio astronomy application. In: 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), 255–260 (2015)Google Scholar
  10. 10.
    Fahmy, S.A., Doyle, L.: Reconfigurable polyphase filter bank architecture for spectrum sensing. In: Sirisuk, P., Morgan, F., El-Ghazawi, T., Amano, H. (eds.) ARC 2010. LNCS, vol. 5992, pp. 343–350. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-12133-3_32CrossRefGoogle Scholar
  11. 11.
    Wu, F., Villing, R.: FPGA based FRM GDFT filter banks. In: 27th Irish Signals and Systems Conference (ISSC) (2016)Google Scholar
  12. 12.
    Wu, F., Palomo-Navarro, Á., Villing, R.: FPGA realization of GDFT-FB based channelizers. In: 26th Irish Signals and Systems Conference (ISSC) (2015)Google Scholar
  13. 13.
    Adámek, K., Novotný, J., Armour, W.: A polyphase filter for many-core architectures. Astron. Comput. 16, 1–16 (2016)CrossRefGoogle Scholar
  14. 14.
    Chennamangalam, J., et al.: A GPU-based wide-band radio spectrometer, vol. 31. Publications of the Astronomical Society of Australia (2014)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute for Information Processing TechnologiesKarlsruhe Institute of TechnologyKarlsruheGermany

Personalised recommendations