@Article{iasc.2021.013009, AUTHOR = {Xiaohong Ji, Junjun Du, Guoqing Jia, Weidong Fang}, TITLE = {Low Complexity Decoding Algorithm for Uplink SCMA Based on Aerial Spherical Decoding}, JOURNAL = {Intelligent Automation \& Soft Computing}, VOLUME = {27}, YEAR = {2021}, NUMBER = {3}, PAGES = {737--746}, URL = {http://www.techscience.com/iasc/v27n3/41650}, ISSN = {2326-005X}, ABSTRACT = {As a new non-orthogonal multiple access technology for 5G massive machine type communication scenario, the sparse code multiple access (SCMA) has greatly improved the spectrum efficiency due to the high connection density. SCMA combines QAM (Quadrature Amplitude Modulation) modulation and sparse spreading into a codebook set to obtain forming gain. The user binary bit data is directly mapped into multi-dimensional codewords in the transmitter. The receiver uses the message passing algorithm (MPA) for multi-user detection to achieve efficient decoding. However, MPA is a good solution for SCMA, though its high complexity limits the application in practical systems. In order to reduce the complexity of MPA, this paper proposed a low-complexity decoding algorithm based on the serial spherical decoding message passing algorithm (SSD-MPA), which greatly enhanced the practicability of the SCMA system. The SSD-MPA took into account the distribution characteristics of the Gaussian noise and the reliability of the constellation points, and only updates the trusted constellation point messages of nodes within the spherical radius. At the same time, it used a serial strategy to speed up the convergence rate. The simulation results have shown that when the radius sets properly, the algorithm reduces the complexity by about 2/3 compared with the original MPA, and the performance was almost lossless.}, DOI = {10.32604/iasc.2021.013009} }