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Deep Neural Network-Based Detector for Single-Carrier Index Modulation NOMA

Gian, T. and Ngo, V.-D. and Nguyen, T.-H. and Nguyen, T.T. and Van Luong, T. (2022) Deep Neural Network-Based Detector for Single-Carrier Index Modulation NOMA. In: Conference of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022, 7 November 2022 Through 10 November 2022, Chiang Mai.

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Abstract

In this paper, a deep neural network (DNN)-based detector for an uplink single-carrier index modulation non-orthogonal multiple access (SC-IM-NOMA) system is proposed, where SC-IM-NOMA allows users to use the same set of sub-carriers for transmitting their data modulated by the sub-carrier index modulation technique. More particularly, users of SC-IM-NOMA simultaneously transmit their SC-IM data at different power levels which are then exploited by their receivers to perform successive interference cancellation (SIC) multi-user detection. The existing detectors designed for SC-IM-NOMA, such as the joint maximum-likelihood (JML) detector and the maximum likelihood SIC-based (ML-SIC) detector, suffer from high computational complexity. To address this issue, we propose a DNN-based detector whose structure relies on the model-based SIC for jointly detecting both M-ary symbols and index bits of all users after trained with sufficient simulated data. The simulation results demonstrate that the proposed DNN-based detector attains near-optimal error performance and significantly reduced runtime complexity in comparison with the existing hand-crafted detectors. © 2022 Asia-Pacific of Signal and Information Processing Association (APSIPA).

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Radio-Electronic Engineering
Identification Number: 10.23919/APSIPAASC55919.2022.9980150
Uncontrolled Keywords: Bit error rate; Complex networks; Maximum likelihood; Multiple access interference; Multiuser detection, Bit-error rate; Deep learning; DeepSIC-IM; Multiple access; NOMA; Non-orthogonal; Non-orthogonal multiple access; Run time complexity; Successive interference cancellations; Uplink, Deep neural networks
Additional Information: Conference of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022 ; Conference Date: 7 November 2022 Through 10 November 2022; Conference Code:185376
URI: http://eprints.lqdtu.edu.vn/id/eprint/10724

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