Short Description

Accurate positioning is a cornerstone of the emerging 5G ecosystem, underpinning use‑cases such as autonomous driving, industrial automation, and location‑based services. Since 3GPP Release 16, the standards body has defined a rich set of positioning procedures (e.g., OTDOA, Uplink‑TDOA, Angle‑of‑Arrival, Multi‑RTT), yet most scholarly contributions remain confined to simulation environments. Consequently, there is a gap between theoretical advances and practical, over‑the‑air validation.

This master’s thesis will close that gap by extending the open‑source srsRAN software‑defined‑radio (SDR) suite with native 5G positioning capabilities. The work will:

1. Survey and select state‑of‑the‑art positioning algorithms compliant with 3GPP Release 16/17.
2. Design and implement new srsRAN modules (positioning service layer, measurement‑report generation, UE‑side positioning engine) that expose the required signaling and processing chains defined by the standards.
3. Integrate the modules into the existing srsRAN stack, ensuring seamless interaction with PHY, MAC, and RRC layers while preserving real‑time constraints.
4. Validate the implementation in a live test‑bed equipped with high‑performance SDR hardware (e.g., USRP X310, LimeSDR‑Mini) capable of transmitting and receiving 5G NR waveforms under realistic propagation conditions.

Deliverables include a fully functional, open‑source positioning extension for srsRAN, a documented experimental framework, and a set of empirical performance results that can be reproduced by other researchers.

Expected Contributions

Methodology Overview

1. Literature Review – Compile a taxonomy of 5G positioning methods and map algorithmic requirements to 3GPP specifications.
2. Requirement Mapping – Align each method with the corresponding RRC/NAS signaling, measurement objects, and reporting criteria.
3. Software Architecture – Extend srsRAN by adding:
   • Positioning Service Layer (RRC extensions)
   • Measurement Processing Blocks (correlators, TDOA estimators)
   • UE Positioning Engine (Kalman/Particle‑filter fusion).
4. Implementation & Optimisation – Develop C++/Python modules.
5. Test‑Bed Deployment – Configure SDRs as gNB and UE, generate controlled reference signals, capture raw IQ data, and feed it into the positioning pipeline.
6. Evaluation – Conduct systematic experiments varying UE mobility; compare results with Monte‑Carlo simulations.

Resources Available

• srsRAN platform with full source‑code access.
• State‑of‑the‑art SDR hardware (USRP X310) supporting 5G NR up to 6 GHz.
• Laboratory space for indoor/outdoor over‑the‑air trials, equipped with GPS reference equipment for ground‑truth positioning.
• Supervision from the telecommunications research group, providing expertise on 3GPP specs and signal‑processing techniques.

Revised Timeline (6 months)

Each month includes weekly progress reviews with the supervisor to ensure alignment and timely issue resolution.

Impact

• Academic: Provides a reproducible platform for future research on 5G/6G positioning, enabling rapid prototyping and validation of novel algorithms.
• Industry: Demonstrates a cost‑effective pathway to integrate positioning services into open‑source RAN solutions, potentially accelerating commercial deployments.
• Community: Contributes valuable code and experimental methodology to the srsRAN ecosystem, fostering collaboration between academia, open‑source developers, and telecom operators.

The six‑month schedule concentrates development and testing phases while still delivering a complete, standards‑compliant positioning extension for srsRAN, together with thorough experimental validation and open‑source release.

For more info see also https://www.sciencedirect.com/science/article/pii/S1389128624004274