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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.17342 |
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| _version_ | 1866912714780049408 |
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| author | Ceresoli, Alberto Bernazzoli, Viola Pegurri, Roberto Filippini, Ilario |
| author_facet | Ceresoli, Alberto Bernazzoli, Viola Pegurri, Roberto Filippini, Ilario |
| contents | Accurate positioning is a key enabler for emerging 5G applications. While the standardized Location Management Function (LMF) operates centrally within the core network, its scalability and latency limitations hinder low-latency and fine-grained localization. A practical alternative is to shift positioning intelligence toward the radio access network (RAN), where uplink sounding reference signal (SRS)-based angle-of-arrival (AoA) estimation offers a lightweight, network-native solution. In this work, we present the first fully open-source 5G testbed for AoA estimation, enabling systematic and repeatable experimentation under realistic yet controllable channel conditions. The framework integrates the NVIDIA Sionna RT with a Keysight PROPSIM channel emulator and includes a novel phase calibration procedure for USRP N310 devices. Experimental results show sub-degree to few-degree accuracy, validating the feasibility of lightweight, single-anchor, network-native localization within next-generation 5G systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_17342 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AoA Services in 5G Networks: A Framework for Real-World Implementation and Systematic Testing Ceresoli, Alberto Bernazzoli, Viola Pegurri, Roberto Filippini, Ilario Networking and Internet Architecture Accurate positioning is a key enabler for emerging 5G applications. While the standardized Location Management Function (LMF) operates centrally within the core network, its scalability and latency limitations hinder low-latency and fine-grained localization. A practical alternative is to shift positioning intelligence toward the radio access network (RAN), where uplink sounding reference signal (SRS)-based angle-of-arrival (AoA) estimation offers a lightweight, network-native solution. In this work, we present the first fully open-source 5G testbed for AoA estimation, enabling systematic and repeatable experimentation under realistic yet controllable channel conditions. The framework integrates the NVIDIA Sionna RT with a Keysight PROPSIM channel emulator and includes a novel phase calibration procedure for USRP N310 devices. Experimental results show sub-degree to few-degree accuracy, validating the feasibility of lightweight, single-anchor, network-native localization within next-generation 5G systems. |
| title | AoA Services in 5G Networks: A Framework for Real-World Implementation and Systematic Testing |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2510.17342 |