Fuzzy C-Means Clustering-Based mMIMO-NOMA Downlink Communication for 6G Ultra-Massive Interconnectivity

Abstract

Cooperation between massive multiple input multiple output (mMIMO) and non-orthogonal multiple access (NOMA) can significantly boost the future sixth-generation (6G) network capacity supporting ultra-massive interconnectivity. Co-operative mMIMO-NOMA has been recently considered in 6G high frequency spectrum such as Millimeter Wave and Terahertz because of its enhanced spectral efficiency property. Moreover, hybrid precoding is used importantly in such communications to reduce the overhead of high power consumption and increase the hardware cost performance. In this paper, we present a sub-array mMIMO-NOMA based downlink network architecture for 6G ultra-massive interconnectivity. A fully-connected hybrid precoding scheme is also considered incorporating with the system which supports equal performance with reduced number of RF chain than a fully-connected digital precoder. In addition, fuzzy c-means clustering algorithm is proposed for huddling the users of the mMIMO-NOMA based communication networks. The algorithm is performed on the received signal strength indicator data set, and the resulting clusters can be used to maximize the power and energy efficiency of the network.