  Spectrum Sensing (SS) constitutes the most critical task i n Cognitive Radio
(CR) systems for Primary User (PU) detection. Cooperative Spectrum Sensing
(CSS) is introduced to enhance the detection reliability of the PU in fading
environments. In this paper, we propose a soft decision based CSS algorithm
using energy detection by taking into account the noise uncertainty effect. In
the proposed algorithm, two threshold levels are utilized based on predicting
the current PU activity, which can be successfully expected using a simple
successive averaging process with time. The two threshold levels are evaluated
based on estimating the noise uncertainty factor. In addition, they are toggled
in a dynamic manner to compensate the noise uncertainty effect and to increase
the probability of detection and decrease the probability of false alarm.
Theoretical analysis is performed on the proposed algorithm to evaluate its
enhanced false alarm and detection probabilities over the conventional soft
decision CSS using different combining schemes. In addition, simulation results
show the high efficiency of the proposed scheme compared to the conventional
soft decision CSS, with high computational complexity enhancements.
