Lee Y., Koo I. (2010) A Neural Network-Based Cooperative Spectrum Sensing Scheme for Cognitive Radio Systems. In: Huang DS., McGinnity M., Heutte L., Zhang XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg
In the single spectrum sensing, it is difficult to overcome obstacles, path loss, deep noise and fading in the network. Cooperative spectrum sensing (CSS) has been proposed as one of solutions to overcome the drawback of the single spectrum sensing. In the CSS, a fusion center collects the sensing information from all secondary users and makes a final decision. Even though CSS can provide better sensing performance than the single spectrum sensing, the problems above mentioned still remain. Thus effective decision method is needed for more adaptive to communication environment. In the paper, we propose a cooperative spectrum sensing utilizing neural network for cognitive radio systems. In the proposed scheme, weight factors of the neural network are trained by using historical sensing information stored on buffer. After that, a final decision is made by using current sensing information as input of neural network. Through the simulation result, we can find the proposed scheme has better performance than other comparison schemes such as AND, OR and half voting rules.
Cognitive radio Cooperative sensing Neural network Multilayer perceptron