Collaborative Research: NeTS-FIND: CogNet - An Experimental Protocol Stack for Cognitive Radio Networks and Its Integration with the Future Internet

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Proposal Number: 0626740PI: Dipankar RaychaudhuriInstitution: Rutgers University (collaborative with Kansas U and CMU)Proposal Number: 0626676PI: Joe EvansInstitution: Kansas University (collaborative with Kansas U and CMU)Proposal Number: 0626827PI: Srini Seshan Institution: CMUTitle: Collaborative NeTS-FIND: CogNet An Experimental Protocol Stack for Cognitive Radio Networks and Its Integration with the Future InternetProject AbstractThis project has two major thrusts: the first is to identify broad architecture and protocol design approaches for cognitive radio networks at both local network and the global internetwork level. This architectural study is intended to lead to the design of control/management and data interfaces between cognitive radio nodes in a local network, and also between cognitive radio subnetworks and the global Internet. The second thrust is to apply these architectural and protocol design results to prototype an open-source cognitive radio protocol (the CogNet stack) and use it for experimental evaluations on emerging cognitive radio platforms. A number of architectural issues are examined as we try to identify an efficient and complete solution these include control and management protocols, support for collaborative PHY, dynamic spectrum coordination, flexible MAC layer protocols, ad hoc group formation and cross-layer adaptation.The experimental component of this project aims to prototype an open-source Linux-based CogNet software protocol stack for use with emerging cognitive radio platforms (such as the GNU/USRP2 radio to be used as the baseline, the KU agile radio or the Lucent/WINLAB network-centric prototype), and make this software available for community research. The prototype software is validated in two steps: first in a wireless local-area radio network scenario with moderate numbers of cognitive radio nodes, and later as part of several end-to-end experiments using a wide-area network testbed such as PlanetLab (and GENI in the future).