文件名称:11
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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.
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.
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11.pdf