Current Volume 8
Abstract
The advent of Reduced Capability (RedCap) devices in 5G networks introduces unique challenges in network slicing due to their constrained computational and communication capabilities. Adaptive network slicing is crucial to optimize resource allocation and maintain quality of service (QoS) for diverse RedCap use cases. Generative Artificial Intelligence (GenAI) presents a promising approach to enhance adaptability by predicting network conditions, automating slice reconfiguration, and optimizing resource distribution dynamically. This paper explores the integration of GenAI models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), to facilitate efficient network slicing for RedCap-enabled 5G networks. GenAI can synthesize realistic network traffic patterns, anticipate congestion, and proactively adjust slice parameters based on learned insights. By leveraging reinforcement learning-driven GenAI models, real-time decision-making can be enhanced, leading to improved spectral efficiency, reduced latency, and optimized power consumption. It present a framework that utilizes GenAI for slice elasticity, ensuring seamless adaptation to changing network conditions while minimizing service disruptions. The proposed approach is evaluated through simulations, demonstrating its effectiveness in dynamically balancing network loads and maintaining QoS in RedCap scenarios. Our findings highlight that GenAI-driven adaptive slicing significantly enhances network efficiency, making 5G RedCap deployments more robust and scalable.
Keywords
Generative AI, Adaptive Network Slicing, RedCap 5G, AI-driven Optimization, and Resource Allocation
Citations
IRE Journals:
Asrar Ahmad Ansari , V. Suresh Kumar
"Leveraging Generative AI for Dynamic Network Slicing in RedCap 5G Networks" Iconic Research And Engineering Journals Volume 8 Issue 10 2025 Page 460-471
IEEE:
Asrar Ahmad Ansari , V. Suresh Kumar
"Leveraging Generative AI for Dynamic Network Slicing in RedCap 5G Networks" Iconic Research And Engineering Journals, 8(10)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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