Performance analysis of spectrum sharing model in cognitive radio networks over fading channels

In this thesis, the spectrum sharing model for cognitive radio networks is investigated. Considering the effect of the interference from the primary network transmitter, ergodic capacity performance for the secondary user is analyzed on the Nakagami-m and Log-Normal distributed fading channels under the average received power constraint. The simulation results obtained by the numerical calculations show that the primary network-generated interference has a significant impact on the ergodic capacity of the secondary users. Ergodic capacity performance for the secondary user is verified by Monte Carlo simulations, taking into account the fading parameter of the Nakagami-m distribution, the standard deviation of the log-normal distribution, and the Lagrange multiplier parameters that determine the optimum power of the secondary user. When evaluated numerical results, it is observed that the performance of the ergodic capacity improves with increasing signal-to-noise ratio. It has been observed that the capacity has deteriorated if the fading parameter of Nakagami- distribution is increased. When the standard deviation of the log-normal distribution was increased, the system performance was positively affected. However, it has been found that the ergodic capacity of the secondary user decreases as the power of interference caused by the primary user transmitter increases in the secondary user receiver. In the study, it is planned to guide the researchers in terms of parameter and channel selection by the effects of the selected fading channels, parameters and the effects of these parameters on the system model by changing their values.