Compressive-Sensing-Based Grant-Free Massive Access for 6G Massive Communication

The envisioned sixth-generation (6G) of wireless communications is expected to give rise to the necessity of connecting very large quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network architectures. In particular, such massive communication has been recognized as a prime driver that can empower the 6G vision of future ubiquitous connectivity, supporting Internet of Human-Machine-Things (IoHMT) for which massive access is critical. This article surveys the most recent advances toward massive access in both academic and industrial communities, focusing primarily on the promising compressive sensing (CS)-based grant-free massive access (GFMA) paradigm. We first specify the limitations of existing random access schemes and reveal that the practical implementation of massive communication relies on a dramatically different random access paradigm from the current ones mainly designed for human-centric communications. Then, a CS-based GFMA roadmap is presented, where the evolutions from single-antenna to large-scale antenna array-based base stations, from single-station to cooperative massive multiple-input-multiple-output (MIMO) systems, and from unsourced to sourced random access scenarios are detailed. Finally, we discuss key challenges and open issues to indicate potential future research directions in GFMA.