Pilot-Less One-Shot Sparse Coding for Short Packet-Based Machine-Type Communications
Jiao Wu, Wonjun Kim, Byonghyo Shim
Abstract
This paper presents a novel transmission scheme to support massive machine-type communications (MTC) devices sending very short packets for Internet-of-Things (IoT) applications. The proposed scheme, termed as pilot-less one-shot (PLOS) transmission, does not require the pilot signaling. The key idea behind PLOS is to encode information into the inter-block nonzero positions and intra-block nonzero positions of a sparse vector. In the receiver, we propose a deep neural network-based scheme, referred to as deep learning-based PLOS (DL-PLOS) to recover the nonzero positions of the sparse vector. From the simulations results, we demonstrate that PLOS is effective in the short packet transmission and DL-PLOS outperforms the conventional greedy algorithms.