Mean-Based Blind Hard Decision Fusion Rules

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.