Published May 13, 2024 | Version v1
Conference paper Open

Centralized and Decentralized ML-Enabled Integrated Terrestrial and Non-Terrestrial Networks

  • 1. ROR icon Istanbul Technical University
  • 2. Vestel (Turkey)
  • 3. ROR icon Istanbul Medipol University
  • 4. ROR icon Turkcell (Turkey)

Description

Non-terrestrial networks (NTNs) are a critical enabler of the persistent connectivity vision of sixth-generation networks, as they can service areas where terrestrial infrastructure falls short. However, the integration of these networks with the terrestrial network is laden with obstacles. The dynamic nature of NTN communication scenarios and numerous variables render conventional model-based solutions computationally costly and impracticable for resource allocation, parameter optimization, and other problems. Machine learning (ML)-based solutions, thus, can perform a pivotal role due to their inherent ability to uncover the hidden patterns in time-varying, multi-dimensional data with superior performance and less complexity. Centralized ML (CML) and decentralized ML (DML), named so based on the distribution of the data and computational load, are two classes of ML that are being studied as solutions for the various complications of terrestrial and non-terrestrial networks (TNTN) integration. Both have their benefits and drawbacks under different circumstances, and it is integral to choose the appropriate ML approach for each TNTN integration issue. To this end, this paper goes over the TNTN integration architectures as given in the 3rd generation partnership project standard releases, proposing possible scenarios. Then, the capabilities and challenges of CML and DML are explored from the vantage point of these scenarios.

Files

Centralized_and_Decentralized_ML-Enabled_Integrated_Terrestrial_and_Non-Terrestrial_Networks.pdf

Additional details

Funding

COMMECT – Bridging the digital divide and addressing the need of Rural Communities with Cost-effective and Environmental-Friendly Connectivity Solutions 101060881
European Commission
Scientific and Technological Research Council of Turkey

Dates

Available
2024-05-13
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