The throughput analysis based on multi-SUs cooperative spectrum prediction for cognitive radio networks
Yang Zhang, Hangsheng Zhao · 2016
Spectrum prediction provides its predicting results to sensing channels selectively for secondary users (SUs). But the results are often inaccurately, further limit the throughput performance of the whole cognitive radio network (CRN). Based on the genetic algorithm optimized training for neural network (GA-NN) spectrum prediction model, a novel cooperative spectrum prediction scheme is proposed. The probability of the SU idle channels sensing is significantly enhanced. The impacts of traffic intensity, cooperative SU number and channel number on the CRN throughput are also investigated respectively in this paper. The simulation results indicate that the throughput with cooperative spectrum prediction is significantly improved compared with traditional spectrum prediction in CRN.