PAPR reduction for MC-CDMA system based on ICSA and Hopfield Neural Network

One of the main implementation disadvantages of a multicarrier communication system is the possibly high peak to average power ratio of the transmitted signals which cause the requirement of highly cost linear amplifiers with large dynamic range. One proposed solution is given by Haiming Wang [1] which is based on the algorithm of Hopfield Neural Network (HNN). Also, in our previous work [2],we demonstrated the solution based on the Immune Clonal Selection Algorithm (ICSA) which has a better performance than [1]. However, a important disadvantage of the ICSA is the need of high number of iteration. In this paper, we will show a hybrid solution which adopts both the concept of ICSA and HNN. According to the simulation results, this solution maintained the good performance of PAPR reduction, meanwhile, the number of iteration is significantly reduced.