Maximizing Throughput Under Power And Interference Constraints In Cognitive Radio Network
Abstract- Cognitive radio is one of the latest technology researchers are using to improve the use of spectrum. In this paper, spectrum efficiency has been enhanced by considering the coexistence of many cognitive radio users and a licensed user. M number of antennas are deployed at the cognitive radio (CR) base station. The downlink sum rate maximizes in the given cognitive radio network while satisfying the signal-to-interference and noise ratio (SINR) constraint as well as limitation of interference to the primary user constraint and at the same time maintaining total power used by CR base station under certain threshold.
The algorithm called Particle Swarm Optimization (PSO) has been used in the system for finding beamforming weights and power allocation for each user simultaneously. The simulation results have been given for three different cases i.e. the number of antennas greater than, equal to and less than the number of CR users. In each case, PSO achieves high throughput quickly and with less complexity as compared to other proposed algorithms like transmit beamforming technique combined with user selection .
Keywords- Cognitive Radio, Interference, Sum-Rate, Base-Station, Beamforming.