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

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Abstract

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.

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Acknowledgments

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.

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Correspondence to Shuoxin Lin.

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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). https://doi.org/10.1007/s11265-014-0938-4

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Keywords

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