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.
Mean-Based Blind Hard Decision Fusion Rules / Mohammad, Fayazur Rahaman; Ciuonzo, Domenico; Mohammed, Zafar Ali Khan. - In: IEEE SIGNAL PROCESSING LETTERS. - ISSN 1070-9908. - 25:5(2018), pp. 630-634. [10.1109/LSP.2018.2809859]
Mean-Based Blind Hard Decision Fusion Rules
Ciuonzo, Domenico;
2018
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
