This repo is the official implementation for Deep neural network-based detector for single-carrier index modulation NOMA, which was published at APSIPA 2022. Its extension was published in the Wireless Networks journal, named DeepSIC-IM. This repository allows researchers and practitioners to reproduce our results as well as a baseline.
Please cite this work if you find it useful.
@INPROCEEDINGS{9980150,
author={Gian, Toan and Ngo, Vu-Duc and Nguyen, Tien-Hoa and Nguyen, Trung Tan and Van Luong, Thien},
booktitle={2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)},
title={Deep Neural Network-Based Detector for Single-Carrier Index Modulation NOMA},
year={2022},
volume={},
number={},
pages={1805-1809},
keywords={Training;NOMA;Maximum likelihood detection;Interference cancellation;Runtime;Simulation;Modulation;Non-orthogonal multiple access;NOMA;uplink;successive interference cancellation;SIC;deep learning;DeepSIC-IM;DNN;bit error rate;runtime complexity},
doi={10.23919/APSIPAASC55919.2022.9980150}}
@article{10.1007/s11276-025-03985-5,
author = {Gian, Toan and Pham, Ngoc-Hung and Pham, Van-Cuong and Nguyen, Tien-Hoa and Nguyen, Trung Tan and Luong, Thien Van},
title = {Deep learning detector for downlink IM-NOMA},
year = {2025},
issue_date = {Aug 2025},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
volume = {31},
number = {6},
issn = {1022-0038},
url = {https://doi.org/10.1007/s11276-025-03985-5},
doi = {10.1007/s11276-025-03985-5},
journal = {Wirel. Netw.},
month = jun,
pages = {4135–4146},
numpages = {12},
keywords = {Non-orthogonal multiple access, NOMA, Downlink, Successive interference cancellation, Data-driven, SIC, Deep learning, DeepIM-SIC, DNN, Bit error rate, Runtime complexity.}
}