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Blind Multi-User Detection for Autonomous Grant-Free High-Overloading Multiple-Access without Reference Signal

In this paper, a novel blind multi-user detection( MUD) framework for autonomous grant-free(AGF) high-overloading non-orthogonal multiple access(NOMA) is introduced in detail aimed at fulfilling the requirements of 5G massive Machine-Type Communication(mMTC)and beyond. From the perspective of the transmitter side,characteristics of diverse types of emerging grant-free transmission, particularly autonomous grant-free(AGF), are elaborated and presented in a comparative manner. In the receiver end, codeword-level successive interference cancellation (CL-SIC) is revealed as the main framework to perform MUD. In addition, underpinning state-of-art blind MUD techniques such as blind activity detection taking advantage of the statistics of the aggregate signals, blind equalization based on the simple geometric characteristics of low order modulation constellation symbols, and blind channel estimation employing the successfully decoded codewords are explained.