Wireless Spectral Prediction by the Modified Echo State Network Based on Leaky Integrate and Fire Neurons

With the rapid development of wireless communication technology, the wireless spectrum resources are dwindling. Cognitive radio (CR) is the key technology to solve this problem. In view of the echo state network advantages compared to traditional recursive neural network, we construct the new neural network, echo state network based on leaky integrate and fire neurons (LIF_ESN), and prove that it has a better network performance, when reduce the reserve pool size and to improve the accuracy for time series prediction problem, than the classic ESN. At the same time, we apply this kind of LIF _ESN to the communication problem. The experimental results show that the ESN and LIF_ESN have good performance on spectral prediction. LIF_ESN can obtain better prediction performance when the reserve pool size is small.