Wavelet-based cognitive SCMA system for mmWave 5G communication networks

Abstract

Fifth generation (5G) communication networks can achieve high spectral efficiency using sparse code multiple access (SCMA) scheme when large number of users are trying to transmit their data simultaneously. The sparsity of SCMA codewords offers the possibility of applying a low-complexity message passing algorithm as an alternative to maximum likelihood detector. However the requirement of densely deployed 5G users is to opportunistically explore new frequencies via cognitive features to overcome spectrum scarcity challenges. In this study spectrum sensing enables cognitive radio capabilities for the SCMA system applied in millimetre wave (mmWave) 5G communications. Proposed cognitive SCMA system can sense the spectrum holes and adapt the transmission in order to utilise the available subcarriers. Besides wavelet packet transform based techniques are used instead of conventional Fourier-based spectrum sensing (FSS) and orthogonal frequency-division multiple access (OFDMA). Wavelet packet spectrum sensing offers more accurate estimation of frequency and power compared with FSS. On the other hand wavelet packet multiple access is more flexible and robust against interference compared with OFDMA. The simulation results verify that the proposed method can significantly improve the performance of SCMA system in terms of probabilities of false alarm and detection and symbol error rate.