H. Issa, M. Shehab and H. Alves, "Meta-Learning Based Few Pilots Demodulation and Interference Cancellation For NOMA Uplink," 2023 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), Gothenburg, Sweden, 2023, pp. 84-89, doi: 10.1109/EuCNC/6GSummit58263.2023.10188320
Meta-learning based few pilots demodulation and interference cancellation for NOMA uplink
|Author:||Issa, Hebatalla1; Shehab, Mohammad1; Alves, Hirley1|
1Centre for Wireless Communications (CWC), University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe20231004138754
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2023-10-04
Non-Orthogonal Multiple Access (NOMA) is at the heart of a paradigm shift towards non-orthogonal communication due to its potential to scale well in massive deployments. Nevertheless, the overhead of channel estimation remains a key challenge in such scenarios. This paper introduces a data-driven, meta-learning-aided NOMA uplink model that minimizes the channel estimation overhead and does not require perfect channel knowledge. Unlike conventional deep learning successive interference cancellation (SICNet), Meta-Learning aided SIC (meta-SICNet) is able to share experience across different devices, facilitating learning for new incoming devices while reducing training overhead. Our results confirm that meta-SICNet outperforms classical SIC and conventional SICNet as it can achieve a lower symbol error rate with fewer pilots.
European Conference on Networks and Communications
|Pages:||84 - 89|
2023 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)
Joint European Conference on Networks and Communications & 6G Summit
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work is partially supported by the Academy of Finland, 6G Flagship program (Grant no. 346208) and FIREMAN (Grant no. 326301), and the European Commission through the Horizon Europe project Hexa-X (Grant Agreement no. 101015956).
|EU Grant Number:||
(101015956) Hexa-X - A flagship for B5G/6G vision and intelligent fabric of technology enablers connecting human, physical, and digital worlds
|Academy of Finland Grant Number:||
346208 (Academy of Finland Funding decision)
326301 (Academy of Finland Funding decision)
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