A Case for Generic Interfaces in Cognitive Radio Networks

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Executive Summary

Cognitive wireless networks are envisioned as a solution for intelligent ubiquitous networks that are capable of adapting to the dynamic environment through programmable radio devices. Each functional module and protocol accomplishes such learning by observing the various environmental, networking and application related parameters and adapts its behavior to improve the performance. While access to a variety of parameters provides a large margin to improve the performance, it hinders the practical use of the system by restricting portability. In this paper, the authors argue that standard generic interfaces can be effectively used to overcome the above problem and enable seamless communication between modules at different layers and radio technologies.

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