Work

Dataflow Modeling and Design for Cognitive Radio Networks

Year: 2013

Type: conference-paper

Abstract: Cognitive radio networks present challenges at many levels of design including configuration, control, and crosslayer optimization. In this paper, we focus primarily on dataflow representations to enable flexibility and reconfigurability in many of the baseband algorithms. Dataflow modeling will be

Source: International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM)

DOI: 10.4108/icst.crowncom.2013.252125

Authors: Lai-Huei Wang, Shuvra Bhattacharyya, Aida Vosoughi, Joseph Cavallaro, Markku Juntti, Jani Boutellier, Olli Silven, Mikko Valkama

Institutions: University of Maryland, College Park, Rice University, University of Oulu, Tampere University of Technology

Language: English

Topic: Cognitive Radio Networks and Spectrum Sensing

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funders: National Science Foundation, Tekes

Awards: EAGER: Collaborative Research: Cross-Layer Modeling and Design of Energy-Aware Cognitive Radio Networks, EAGER: Collaborative Research: Cross-Layer Modeling and Design of Energy-Aware Cognitive Radio Networks

OpenAlex ID: W2082682530

FWCI: 0.511

Cites: 20

Cited by: 3

Related to: 10