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https://dspace.iiti.ac.in/handle/123456789/13023
| Title: | Performance Analysis and Learning-Assisted Power Control for NOMA Enabled D2D-Cellular Network |
| Authors: | Jose, Justin Bhatia, Vimal |
| Keywords: | Decoding;Device-to-device communication;Fading channels;Interference cancellation;Nakagami-m fading;NOMA;nonorthogonal multiple access (NOMA);outage probability;Protocols;Symbols |
| Issue Date: | 2023 |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Citation: | Jose, J., Agarwal, A., Shaik, P., Goyal, V., Choi, K., & Bhatia, V. (2023). Performance Analysis and Learning-Assisted Power Control for NOMA Enabled D2D-Cellular Network. IEEE Systems Journal. Scopus. https://doi.org/10.1109/JSYST.2023.3331123 |
| Abstract: | This work investigates a device-to-device (D2D) underlayed cellular system where both D2D and cellular networks are NOMA enabled, which is not only more spectrally efficient than the previous D2D and NOMA models but also can outperform them. Specifically, we first present closed-form expressions for system outage probability (SOP) and sum ergodic rate (SER) metrics for performance analysis and thereafter propose a deep neural network-based power control mechanism for SOP minimization. Analytical results are validated with extensive simulations that reveal the effectiveness of the proposed model over comparative schemes and the requirement of optimizing the power values in accordance with change in different system parameters. IEEE |
| URI: | https://doi.org/10.1109/JSYST.2023.3331123 https://dspace.iiti.ac.in/handle/123456789/13023 |
| ISSN: | 1932-8184 |
| Type of Material: | Journal Article |
| Appears in Collections: | Department of Electrical Engineering |
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