Article Dans Une Revue (Article De Synthèse) IEEE Internet of Things Journal Année : 2025

Positioning in 5G Networks: Emerging Techniques, Use Cases, and Challenges

Résumé

As 5G networks proliferate globally, the need for accurate, reliable, and scalable positioning solutions has become increasingly critical across industries such as IoT, healthcare, and autonomous systems. This paper comprehensively reviews current and emerging positioning techniques within 5G, exploring the advancements enabled by sidelink communication, Reconfigurable Intelligent Surfaces (RIS), machine learning, and massive MIMO. We examine the evolution of 5G positioning as defined by key 3GPP releases, and provide a comparative analysis of the techniques in terms of accuracy, cost, and robustness. The review also highlights key challenges, including non-line-of-sight (NLOS) environments, real-time data processing, and security concerns, which must be addressed for widespread adoption. Finally, we discuss future directions for 5G-Advanced and 6G positioning technologies, offering insights into potential improvements and the ongoing evolution of the field.

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Dates et versions

hal-04948666 , version 1 (18-02-2025)

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Mohammad Abuyaghi, Samir Si-Mohammed, George Shaker, Catherine Rosenberg. Positioning in 5G Networks: Emerging Techniques, Use Cases, and Challenges. IEEE Internet of Things Journal, 2025, 12 (2), pp.1408-1427. ⟨10.1109/JIOT.2024.3487822⟩. ⟨hal-04948666⟩
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