skip to main content
research-article

RapidRadio: Signal Classification and Radio Deployment Framework

Published:01 August 2012Publication History
Skip Abstract Section

Abstract

In this article, the RapidRadio framework for signal classification and receiver deployment is discussed. The framework is a productivity-enhancing tool that reduces the required knowledge base for implementing a receiver on an FPGA-based SDR platform. The ultimate objective of this framework is to identify unknown signals and to build FPGA-based receivers capable of receiving them. RapidRadio divides the process of radio creation into two phases; the analysis phase and radio synthesis phase. The analysis phase guides the user through the process of classifying an unknown signal and determining its modulation scheme and parameters, resulting in a radio receiver model. In the second phase, this model is transformed into a functional receiver in an FPGA-based platform.

References

  1. Bergamaschi, R., Lee, W., Richardson, D., Bhattacharya, S., Muhlada, M., Wagner, R., Weiner, A., and White, F. 2000. Coral-automating the design of systems-on-chip using cores. In Proceedings of the IEEE Custom Integrated Circuits Conference (CICC). 109--112.Google ScholarGoogle Scholar
  2. Brookner, E. 1998. Tracking and Kalman Filtering Made Easy. John Wiley & Sons, Hoboken, NJ.Google ScholarGoogle Scholar
  3. CLIPS. 2007. CLIPS Reference Manual: Volume I Basic Programming Guide.Google ScholarGoogle Scholar
  4. Dick, C. and Harris, F. 2002. FPGA QAM demodulator design. In Field-Programmable Logic and Applications: Reconfigurable Computing Is Going Mainstream. Lecture Notes in Computer Science, vol. 2438, Springer, Berlin, 279--287. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Dick, C., Harris, F., and Rice, M. 2004. FPGA implementation of carrier synchronization for QAM receivers. J. VLSI Sig. Proc. 36, 1, 57--71. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Dobre, O., Abdi, A., Bar-Ness, Y., and Su, W. 2007. Survey of automatic modulation classification techniques: Classical approaches and new trends. Communications IET 1, 2, 137--156.Google ScholarGoogle ScholarCross RefCross Ref
  7. Fehske, A., Gaeddert, J., and Reed, J. H. 2005. A new approach to signal classification using spectral correlation and neural networks. In Proceedings of the 1st IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN). 144--150.Google ScholarGoogle Scholar
  8. Gardner, F. 1986. A BPSK/QPSK timing-error detector for sampled receivers/qpsk timing-error detector for sampled receivers. IEEE Trans. Commun. 34, 5, 423--429.Google ScholarGoogle ScholarCross RefCross Ref
  9. Godard, D. 1978. Passband timing recovery in an all-digital modem receiver. IEEE Trans. Commun. 26, 5, 517--523.Google ScholarGoogle ScholarCross RefCross Ref
  10. Huo, X. and Donoho, D. 1998. A simple and robust modulation classification method via counting. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 6, 3289--3292.Google ScholarGoogle Scholar
  11. Kim, K., Akbar, I. A., Bae, K. K., Um, J.-S., Spooner, C. M., and Reed, J. H. 2007. Cyclostationary approaches to signal detection and classification in cognitive radio. In Proceedings of the 2nd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN). 212--215.Google ScholarGoogle Scholar
  12. Liu, L. and Xu, J. 2006. A novel modulation classification method based on high order cumulants. In Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing (WiCom’06). 1--5.Google ScholarGoogle Scholar
  13. Minden, G. J., Evans, J., Searl, L., DePardo, D., Petty, V., Rajbanshi, R., Newman, T., Chen, Q., Weidling, F., Guffey, J., Datla, D., Barker, B., Peck, M., Cordill, B., Wyglinski, A., and Agah, A. 2007. KUAR: A flexible software-defined radio development platform. In Proceedings of the 2nd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN).Google ScholarGoogle Scholar
  14. Pawula, R., Rice, S., and Roberts, J. 1982. Distribution of the phase angle between two vectors perturbed by gaussian noise. IEEE Trans. Commun. 30, 8, 1828--1841.Google ScholarGoogle ScholarCross RefCross Ref
  15. Recio, A., Surís, J., and Athanas, P. 2009. Blind signal parameter estimation for the rapid radio framework. In Proceedings of the IEEE Military Communications Conference (MilCom’09). Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Simon, M. 2005. Noncoherent symbol synchronization techniques. In Proceedings of the IEEE Military Communications Conference (MilCom’05). 3321--3327.Google ScholarGoogle ScholarCross RefCross Ref
  17. Stoica, P. and Moses, R. 2005. Spectral Analysis of Signals. Prentice Hall, Upper Saddle River, NJ, Chapter 2, 52--53.Google ScholarGoogle Scholar
  18. Swami, A. and Sadler, B. M. 2000. Hierarchical digital modulation classification using cumulants. IEEE Trans. Commun. 48, 3, 416--429.Google ScholarGoogle ScholarCross RefCross Ref
  19. Tachwali, Y., Barnes, W., and Refai, H. 2009. Configurable symbol synchronizers for software-defined radio applications. J. Netw. Comput. Appl. 32, 3, 607--615. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Umebayashi, K., Lehtomaki, J., and Ruotsalainen, K. 2006. Analysis of minimum Hellinger distance identification for digital phase modulation. In Proceedings of the IEEE International Conference on Communications (ICC’06). 2952--2956.Google ScholarGoogle Scholar
  21. Xilinx Inc. 2007. System Generator for DSP: Getting Started Guide. Xilinx Inc.Google ScholarGoogle Scholar
  22. Zicari, P., Sciagura, E., Perri, S., and Corsonello, P. 2008. A programmable carrier phase independent symbol timing recovery circuit for {qpsk/oqpsk} signals. Microprocess. Microsyst. 32, 8, 437--446. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. RapidRadio: Signal Classification and Radio Deployment Framework

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    Full Access

    • Published in

      cover image ACM Transactions on Embedded Computing Systems
      ACM Transactions on Embedded Computing Systems  Volume 11, Issue S2
      Special Section on CAPA'09, Special Section on WHS'09, and Special Section VCPSS' 09
      August 2012
      396 pages
      ISSN:1539-9087
      EISSN:1558-3465
      DOI:10.1145/2331147
      Issue’s Table of Contents

      Copyright © 2012 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 1 August 2012
      • Accepted: 1 January 2010
      • Revised: 1 December 2009
      • Received: 1 June 2009
      Published in tecs Volume 11, Issue S2

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed
    • Article Metrics

      • Downloads (Last 12 months)1
      • Downloads (Last 6 weeks)1

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader
    About Cookies On This Site

    We use cookies to ensure that we give you the best experience on our website.

    Learn more

    Got it!