Description
Matlab Simulation Codes of CNN for OFDM-SPM
As the demand for higher data rates has rapidly been increasing day after day, researchers around the world have given serious attention and made significant efforts towards exploring new techniques that can improve the spectral efficiency of future wireless systems. Among these methods, the modulation technique termed OFDM-SPM is considered as a key potential candidate transmission method that can effectively improve the per-user spectral efficiency of wireless networks. However, the reliability performance efficiency of OFDM-SPM is not that high despite using two dimensions to send data, it was found that the additional data stream conveyed by sub-carriers power has a higher bit error rate (BER) performance compared to the data stream conveyed by conventional modulation schemes. To improve the reliability performance of OFDM-SPM Furthermore, in this paper, we propose the use of CNN based equalizer for OFDM-SPM.
As deep learning techniques, such as Convolutional Neural Networks (CNN) are applied to OFDM-SPM, Simulation results have shown that Convolutional Neural Networks (CNN) based equalizers can improve the reliability performance of OFDM-SPM by 5-10 dB compared to the conventional scheme that does not use CNN.
