Name
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TVT.2020.2995840 | IEEE Transactions on Vehicular Technology |
Keywords | DocType | Volume |
Machine-type communications (MTC),short packet transmission,deep neural network (DNN)-based decoding | Journal | 69 |
Issue | ISSN | Citations |
8 | 0018-9545 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiao Wu | 1 | 0 | 2.03 |
| Wonjun Kim | 2 | 301 | 26.50 |
| Byonghyo Shim | 3 | 937 | 88.51 |