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All Journal International Journal of Engineering, Science and Information Technology
Mishra, Smita
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Energy-Efficient Protocols for Massive IOT Connectivity in 6G Networks Ravilla, Lokesh; Upadhyay, Satish; Louis, Magthelin Therase; Swain, Biswaranjan; Mamatha, G. N.; Mishra, Smita; Aneja, Aseem
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1449

Abstract

The possible evolution in wireless communication as it approaches sixth-generation (6G) networks highlights remarkable features, including one of device connectivity, ultra-low latency, and energy efficiency, enabling mIoT deployment. However, these features come with a myriad of challenges with the integration of billions of constrained IoT devices, especially in relation to the aforementioned energy hurdles alongside scalability and spectrum efficiency. This work focuses on energy-efficient 6G IoT networks, proposing new low-power adaptive communication protocols, emphasising power adaptive performance, dependability, and trustworthiness. The roles of key facilitators, Reconfigurable Intelligent Surfaces (RIS), Non-Orthogonal Multiple Access (NOMA), machine learning coupled with energy harvesting, and even off-grid sustainable power sources are critical for enhanced sustainable connectivity. Covering the protocol design in the physical, MAC, and network layers permits the highlighting of cross-layer optimisation IoT ecosystems in 6G and the focused attention IoT research lacks, supporting bold, environmentally sustainable infrastructure designs.
Beyond 5G: Exploring AI-Driven Network Optimisation for 6G Communications Meher, Kunal; Karthikeyan, S.; Ranjan Sahu, Bharat Jyoti; Sunil, M.P.; Mishra, Smita; Singh, Amanveer; Tejesh, Kukatla
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1305

Abstract

This research consists of various features of 5G networks; the vision for 6G networks promises significant advancements, including ultra-high data rates, sub-millisecond latency, highly intelligent network operations, and exceptional device interconnectivity, among others.  Artificial Intelligence (AI) meets these requirements, which act as a fundamental base in self-organising and proactive adaptive network management. In the scope of this paper, AI integration with core 6G network functions is considered, including AI techniques such as machine learning, deep learning, federated learning, and reinforcement learning. Focus is on the AI-driven optimisation of spectrum utilisation, user experience, traffic pattern prediction, dynamic network slicing, robust QoS, and responsive QoS retention. Advancing edge computing, reconfigurable intelligent surfaces (RIS), and digital twins are also discussed. The study also discusses the lack of AI governance in 6G infrastructure, which includes data privacy, transparency of the algorithms, energy expenses, and global standardisation. This research focus reveals the highlights of the primary gaps in design and governance rationale that emerge through the lack of AI-integrated structural frameworks, resigns through the absence of a designed fabric needed to supplant the transcending potential of 6G enabled autonomous communication systems AI will irrevocably purge and define the naivety behind detonating the boundless potential AI entrenched paradigms will deliver.
Co-Authors Aneja, Aseem Karthikeyan, S. Louis, Magthelin Therase Mamatha, G. N. Meher, Kunal Ranjan Sahu, Bharat Jyoti Ravilla, Lokesh Singh, Amanveer Sunil, M.P. Swain, Biswaranjan Tejesh, Kukatla Upadhyay, Satish