Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Parameterized Sets of Dataflow Modes And Their Application to Implementation of Cognitive Radio Systems

  • 496 Accesses

  • 9 Citations


Cognitive radio networks present challenges at many levels of design, including configuration, control, and cross-layer optimization. To meet requirements of bandwidth, flexibility and reconfigurability, systematic methods to model and analyze cognitive radio designs on signal processing platforms are desired. To help address these challenges, we present in this paper a novel dataflow modeling technique, called parameterized set of modes (PSM). PSMs allow efficient representation, manipulation and application of related groups of processing configurations for functional design components in signal processing systems. PSMs lead to more concise formulations of actor behavior, and a unified modeling methodology for applying a variety of techniques for efficient implementation. We develop the formal foundations of PSM-based modeling, and demonstrate its utility through two case studies involving the mapping of reconfigurable wireless communication functionality into efficient implementations.

This is a preview of subscription content, log in to check access.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8


  1. 1.

    van de Beek, J.J., Sandell, M., Isaksson, M., Borjesson, P.O. (1995). Low-complex frame synchronization in OFDM systems. In: Proceedings of the International Conference on Universal Personal Communications, pp. 982–986.

  2. 2.

    Bhattacharya, B., & Bhattacharyya, S.S. (2001). Parameterized dataflow modeling for DSP systems. IEEE Transactions on Signal Processing, 49(10), 2408–2421. doi:10.1109/78.950795.

  3. 3.

    (2013) In Bhattacharyya, S.S., Deprettere, E., Leupers, R., Takala, J. (Eds.), Handbook of Signal Processing Systems, 2nd: Springer. ISBN: 978-1-4614-6858-5 (Print); 978-1-4614-6859-2 (Online). doi:10.1007/978-1-4614-6859-2.

  4. 4.

    Bhattacharyya, S.S., Murthy, P.K., Lee, E.A. (1999). Synthesis of embedded software from synchronous dataflow specifications. Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 21(2), 151–166.

  5. 5.

    Bilsen, G., Engels, M., Lauwereins, R., Peperstraete, J.A. (1996). Cyclo-static dataflow. IEEE Transactions on Signal Processing, 44(2), 397–408.

  6. 6.

    Blajić, T., Nogulić, D., DruŻijanić, M. (2006). Latency improvements in 3G long term evolution. In: Proceedings of the International Convention on Information and Communication Technology, Electronics and Microelectronics.

  7. 7.

    Buck, J.T., & Lee, E.A. (1993). In Scheduling dynamic dataflow graphs using the token flow model. In: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing.

  8. 8.

    Edfors, O., Sandell, M., van de Beek, J.J., Landstrom, D., Sjoberg, F. (1996). An introduction to orthogonal frequency division multiplexing. Tech. rep. Sweden: Lulea University of Technology.

  9. 9.

    Eker, J., & Janneck, J.W. (2003). CAL language report, language version 1.0 — document edition 1. Tech. Rep. UCB/ERL M03/48, Electronics Research Laboratory, University of California at Berkeley.

  10. 10.

    Falk, J., Zebelein, C., Haubelt, C., Teich, J. (2013). A rule-based quasi-static scheduling approach for static islands in dynamic dataflow graphs. ACM Transactions on Embedded Computing Systems, 12(3).

  11. 11.

    Gu, R., Janneck, J., Raulet, M., Bhattacharyya, S.S. (2009). Exploiting statically schedulable regions in dataflow programs, (pp. 565–568). Taiwan: Taipei.

  12. 12.

    Haubelt, C., Falk, J., Keinert, J., Schlichter, T., Streubuhr̈, M., Deyhle, A., Hadert, A., Teich, J. (2007). A SystemC-based design methodology for digital signal processing systems. EURASIP Journal on Embedded Systems 2007, Article ID, 47(580), 22.

  13. 13.

    Lee, E.A., & Messerschmitt, D.G. (1987). Synchronous dataflow. Proceedings of the IEEE, 75(9), 1235–1245.

  14. 14.

    Plishker, W., Sane, N., Bhattacharyya, S.S. (2009). Mode grouping for more effective generalized scheduling of dynamic dataflow applications. In: Proceedings of the Design Automation Conference, pp. 923–926. San Francisco.

  15. 15.

    Plishker, W., Sane, N., Kiemb, M., Anand, K., Bhattacharyya, S.S. (2008). Functional DIF for rapid prototyping, (pp. 17–23). California: Monterey.

  16. 16.

    Plishker, W., Sane, N., Kiemb, M., Bhattacharyya, S.S. (2008). Heterogeneous design in functional DIF, (pp. 157–166). Greece: Samos.

  17. 17.

    Ritz, S., Pankert, M., Meyr, H. (1993). Optimum vectorization of scalable synchronous dataflow graphs.

  18. 18.

    Sane, N., Hsu, C., Pino, J.L., Bhattacharyya, S.S. (2010). Simulating dynamic communication systems using the core functional dataflow model, (pp. 1538–1541). Texas: Dallas.

  19. 19.

    Shen, C., Plishker, W., Wu, H., Bhattacharyya, S.S. (2010). A lightweight dataflow approach for design and implementation of SDR systems, (pp. 640–645). Washington DC : USA.

  20. 20.

    Shen, C., Wang, L., Cho, I., Kim, S., Won, S., Plishker, W., Bhattacharyya, S.S. (2011). In The DSPCAD lightweight dataflow environment: Introduction to LIDE version 0.1. Tech. Rep. UMIACS-TR-2011-17, Institute for Advanced Computer Studies: University of Maryland at College Park.

  21. 21.

    Siyoum, F., Geilen, M., Moreira, O., Nas, R., Corporaal, H. (2011). Analyzing synchronous dataflow scenarios for dynamic software-defined radio applications. In: Proceedings of the International Symposium on System-on-Chip, pp. 14–21.

Download references


This work was supported in part by the US National Science Foundation under grants CNS–1265332 and CNS–1264486; Tekes — the Finnish Funding Agency for Technology and Innovation — through the WiFiUS program; and the Laboratory for Telecommunications Sciences.

We are also grateful the anonymous reviewers for their constructive comments, which have helped significantly to improve the paper.

Author information

Correspondence to Shuoxin Lin.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lin, S., Wang, L., Vosoughi, A. et al. Parameterized Sets of Dataflow Modes And Their Application to Implementation of Cognitive Radio Systems. J Sign Process Syst 80, 3–18 (2015).

Download citation


  • Cognitive radio
  • Dataflow graphs
  • Embedded signal processing
  • Heterogeneous multiprocessors
  • Model-based design