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<span class="release-stage" >pre-print</span>
The proliferating number of devices with short payloads as well as low power budget has already driven researchers away from classical grant-based access schemes that are notorious for their large signalling overhead as well as power-consuming retransmissions. Instead, light-weight random access protocols have been re-investigated and their throughput has been improved in orders of magnitude with sophisticated yet still low-complex transceiver algorithms. In fact, grant-free access has been<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.10257v1">arXiv:2003.10257v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/owtfsqzvsjgqfacacriw5z24uu">fatcat:owtfsqzvsjgqfacacriw5z24uu</a> </span>
more »... tified as a key medium access control technique for providing massive connectivity in machine type communications in cellular networks. In this paper, we show that grant-free access combined with non-orthogonal transmission schemes is a promising solution for 6G Internet of Things (IoT). We present novel and promising results for deep learning (DL)-based techniques for joint user detection and decoding. Then, we propose a multi-layered model for GF-NOMA for power-efficient communications. We also discuss resource allocation issues to enable the co-existence of GF-NOMA with other orthogonal or even grant-based schemes. Finally, we conclude with proposed research directions for medium access towards enabling 6G-IoT.
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