Sinha Namrata Ieee Access Link Jun 2026

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This paper presents an energy-efficient resource allocation scheme for IoT networks using machine learning techniques. The proposed scheme uses a deep reinforcement learning approach to optimize the resource allocation and reduce energy consumption. The paper has been widely cited and has received over 300 citations.

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: She co-authored work on AI-enhanced blockchain consensus , which serves as an informative analysis of how autonomous threat prevention can protect digital ecosystems.

In this survey article, Sinha Namrata provides an overview of artificial intelligence-based techniques for resource allocation in 5G networks. The article discusses various machine learning algorithms and their applications in resource allocation, network slicing, and traffic prediction.