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

As 5G networks proliferate globally, the need for accurate, reliable, and scalable positioning solutions has become increasingly critical across industries, such as Internet of Things (IoT), healthcare, and autonomous systems. This article comprehensively reviews current and emerging positioning techniques within 5G, exploring the advancements enabled by sidelink communication, reconfigurable intelligent surfaces (RISs), machine learning, and massive multiple-input–multiple-output. 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.

I. Introduction

Recent years have seen a remarkable proliferation of cellular communication technologies and new devices, some with very sophisticated capabilities while others are very simple, giving rise to a plethora of use cases. This proliferation showcases how connectivity is revolutionizing various aspects of our daily lives. This article focuses on positioning in 5G and beyond, discussing emerging technologies and their applications.