Spectrum　sensing　is　a　crucial　technology　in　cognitive　radio　(CR).　Cumulant-based　or　higher　order　statistics　(HOS)　based　spectrum　sensing　methods　are　often　considered　in　literature　for　spectrum　sensing　because　cumulants　higher　than　3-order　can　be　used　as　a　feature　to　distinguish　non-Gaussian　signals　from　Gaussian　noise.　However,　most　existing　cooperative　spectrum　sensing　methods　are　based　on　the　assumption　that　the　channel　gain　is　available,　which　cannot　be　realistic　in　practice.　In　this　paper,　a　novel　cumulant-based　cooperative　spectrum　sensing　method　is　proposed.　The　proposed　method　does　not　depend　on　the　noise　power,　channel　gain,　or　the　unknown　signal　parameters.　Additionally,　the　proposed　method　is　based　on　Neyman-Pearson　(N-P)　criteria,　thus　it　is　optimal　in　terms　of　the　performance　of　detection　probability　if　the　false　alarm　probability　is　given　in　advance.　Simulation　results　and　analysis　are　presented　to　verify　the　validity　and　the　superiority　of　the　proposed　cooperative　spectrum　sensing　method　over　the　existing　ones.　(C)　2017　Published　by　Elsevier　B.V.