Performance Analysis and Learning-Assisted Power Control for NOMA Enabled D2D-Cellular Network

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50021057" target="_blank" >RIV/62690094:18450/24:50021057 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10341543/" target="_blank" >https://ieeexplore.ieee.org/document/10341543/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/JSYST.2023.3331123" target="_blank" >10.1109/JSYST.2023.3331123</a>

Result language
angličtina
Original language name
Performance Analysis and Learning-Assisted Power Control for NOMA Enabled D2D-Cellular Network
Original language description
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.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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