Mean-Based Blind Hard Decision Fusion Rules

Mohammad, Fayazur Rahaman and Ciuonzo, Domenico and Khan, Mohammed Zafar Ali (2018) Mean-Based Blind Hard Decision Fusion Rules. IEEE Signal Processing Letters, 25 (5). pp. 630-634. ISSN 1070-9908

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Abstract

In this letter, we propose novel (semi) blind hard decision fusion rules that use the mean of the secondary user characteristics instead of their actual values. We show that these rules with slight (or no) additional system knowledge achieve better receiver operating characteristics than existing (semi) blind alternatives. These rules also have a low-complexity analytical solution under Neyman-Pearson criterion in some relevant cases. Numerical results are reported in a channel-aware scenario to demonstrate their appeal and to confirm the theoretical findings.

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IITH Creators:	IITH Creators ORCiD Khan, Mohammed Zafar Ali UNSPECIFIED
Item Type:	Article
Uncontrolled Keywords:	Cognitive radio, decision fusion, hypothesis testing, knapsack, Neyman-Pearson, nonrandomized tests
Subjects:	Electrical Engineering
Divisions:	Department of Electrical Engineering
Depositing User:	Team Library
Date Deposited:	26 Apr 2018 03:38
Last Modified:	26 Apr 2018 04:37
URI:	http://raiithold.iith.ac.in/id/eprint/3888
Publisher URL:	http://doi.org/10.1109/LSP.2018.2809859
OA policy:	http://www.sherpa.ac.uk/romeo/issn/1070-9908/
Related URLs:	Google Scholar

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