Genetic Algorithm for Selecting Optimal Secondary Users to Collaborate in Spectrum sensing

Sammanfattning: Cognitive Radio is an innovative technology that allows the secondary unlicensed users to share the spectrum with licensed primary users to utilize the spectrum. For maximum utilization of spectrum, in cognitive radio network spectrum sensing is an important issue. Cognitive user under extreme shadowing and channel fading can‟t sense the primary licensed user signal correctly and thus to improve the performance of spectrum sensing, collaboration between secondary unlicensed users is required. In collaborative spectrum sensing the observation of each secondary user is received by a base station acting as a central entity, where a final conclusion about the presence or absence of the primary user signal is made using a particular decision and fusion rule. Due to spatially correlated shadowing the collaborative spectrum sensing performance decreases, and thus optimum secondary users must be selected to, not only improve spectrum sensing performance but also lessen the processing overhead of the central entity. A particular situation is depicted in the project where according to some performance parameters, first those optimum secondary users that have enough spatial separation and high average received SNR are selected using Genetic Algorithm, and then collaboration among these optimum secondary users is done to evaluate the performance. The collaboration of optimal secondary user providing high probability of detection and low probability of false alarm, for sensing the spectrum is compared with the collaboration of all the available secondary users in that radio environment. At the end a conclusion has been made that collaboration of selected optimum secondary users provides better performance, then the collaboration of all the secondary users available.