  One of the most important technical challenges when designing a Cognitive
Radio Networks (CRNs) is spectrum sensing, which has the responsibility of
recognizing the presence or absence of the primary users in the frequency
bands. A common technique used for spectrum sensing is double energy detection
since it can operate without any prior information regarding the
characteristics of the primary user signals. A double threshold energy
detection algorithm is based on the use of two thresholds, to check the energy
of the received signals and decided whether the spectrum is occupied or not.
Furthermore, thresholds play a key role in the energy detection algorithm, by
considering the stochastic features of noise in this model, as a result
calculating the optimal threshold is a crucial task. In this paper, the
Bi-Section algorithm was used to detect the optimum energy level in the fuzzy
region which is an area between the low and high energy threshold. For this
purpose, the decision threshold was determined by the use of the Bisection
function for cognitive users. Numerical simulations show that the proposed
method achieves better detection performance than the conventional
double-threshold energy-sensing schemes. Moreover, the presented technique has
advantages such as increasing the probability of detection of primary users and
decreasing the probability of Collison between primary and secondary users.
