Estimation of Optimal Channel Gain in Cognitive Radio Networks Using Bisectional Algorithm

In Cognitive radio network, to carry out spectrum sharing between the primary users and cognitive users the interference temperature must be known. When Cognitive Transmitter (CT) knows the interference temperature, it will be able to share the spectrum along with the Primary Transmitter (PT) without affecting the quality of service of the primary users. So, to determine interference temperature from the cognitive transmitter, the primary channel gain must be calculated from the CT. To calculate the primary channel gain a maximum likelihood estimator (MLE) has been designed. In order to reduce the complexity of the maximum likelihood (ML) estimator, a Bisectional algorithm has been introduced to estimate the optimal channel gain from CT. The estimation error is very less of about -0.88 and it is reduced to -0.92 as the number of block increases to 100. The channel gain approaches to true value, when the number of blocks increases to 100. The achieved rate of CT is 18 kbps and the estimator approaches to true value as L block increases with perfect primary channel gain.