Abstract
This study explores implementing a digital twin network (DTN) for efficient 6 G wireless network management, aligning with the fault, configuration, accounting, performance, and security (FCAPS) model. The DTN architecture comprises the Physical Twin Layer, implemented using NS-3, and the Service Layer, featuring machine learning and reinforcement learning for optimizing carrier sensitivity threshold and transmit power control in wireless networks. We introduce a robust 'What-if Analysis' module, utilizing conditional tabular generative adversarial network for synthetic data generation to mimic various network scenarios. These scenarios assess four network performance metrics: throughput, latency, packet loss, and coverage. Our findings demonstrate the efficiency of the proposed what-if analysis framework in managing complex network conditions, highlighting the importance of the scenario-maker and the impact of twinning intervals on network performance.
Original language | English |
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Title of host publication | 20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 232-237 |
Number of pages | 6 |
ISBN (Electronic) | 9798350361261 |
DOIs | |
Publication status | Published - 2024 |
Event | 20th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2024 - Hybrid, Ayia Napa, Cyprus Duration: 27 May 2024 → 31 May 2024 |
Publication series
Name | 20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024 |
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Conference
Conference | 20th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2024 |
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Country/Territory | Cyprus |
City | Hybrid, Ayia Napa |
Period | 27/05/24 → 31/05/24 |
Bibliographical note
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