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Binary is good: A binary inference framework for...
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Binary is good: A binary inference framework for primary user separation in cognitive radio networks

Abstract

Primary users (PU) separation concerns with the issues of distinguishing and characterizing primary users in cognitive radio (CR) networks. We argue the need for PU separation in the context of collaborative spectrum sensing and monitor selection. In this paper, we model the observations of monitors as boolean OR mixtures of underlying binary latency sources for PUs, and devise a novel binary inference algorithm for PU separation. Simulation …

Authors

Nguyen H; Zheng R; Han Z

Pagination

pp. 1-5

Publisher

European Alliance for Innovation n.o.

Publication Date

January 1, 2010

DOI

10.4108/icst.crowncom2010.9248

Name of conference

Proceedings of the 5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications