In this paper, we analyze the performance of

spectrum sensing based on energy detection. We do not assume

the exact noise variance is known a priori. Instead, an estimated

noise variance is used to calculate the threshold used in the

spectrum sensing based on energy detection. We propose a new

analytical model to uate the statistical performance of the

energy detection. We claim some characteristics of this model,

and analyze how these characteristics affect the performance of

spectrum sensing. The analytical results are verified through

numerical examples and simulations. Through these examples,

we demonstrate the effectiveness of our analytical model: we

show how it can be used to set the appropriate threshold such

that more spectrum sharing can be facilitated, especially when

combined with cooperative spectrum sensing method.-In this paper, we analyze the performance of

spectrum sensing based on energy detection. We do not assume

the exact noise variance is known a priori. Instead, an estimated

noise variance is used to calculate the threshold used in the

spectrum sensing based on energy detection. We propose a new

analytical model to　uate the statistical performance of the

energy detection. We claim some characteristics of this model,

and analyze how these characteristics affect the performance of

spectrum sensing. The analytical results are verified through

numerical examples and simulations. Through these examples,

we demonstrate the effectiveness of our analytical model: we

show how it can be used to set the appropriate threshold such

that more spectrum sharing can be facilitated, especially when

combined with cooperative spectrum sensing method.