ReviewSensors (Basel, Switzerland)2022
Positioning in 5G and 6G Networks-A Survey.
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- An Efficient Uplink 3D AoA Positioning Framework for 5G RedCap UEs in Indoor Factory Environments.Sensors (Basel, Switzerland) · 2026Article
- Indoor positioning with multi-domain CSI-based deep attention networks for MIMO wireless systems.NPJ wireless technology · 2026Article
- DL-AoD Estimation-Based 5G Positioning Using Directionally Transmitted Synchronization Signals.Sensors (Basel, Switzerland) · 2025Article
- 5G Indoor Positioning Error Correction Based on 5G-PECNN.Sensors (Basel, Switzerland) · 2024Article
- 5G Positioning: An Analysis of Early Datasets.Sensors (Basel, Switzerland) · 2023Article
- A feasibility study of 5G positioning with current cellular network deployment.Scientific reports · 2023Article
- Large-Scale Cellular Vehicle-to-Everything Deployments Based on 5G-Critical Challenges, Solutions, and Vision towards 6G: A Survey.Sensors (Basel, Switzerland) · 2023Article
- Positioning with GNSS and 5G: Analysis of Geometric Accuracy in Urban Scenarios.Sensors (Basel, Switzerland) · 2023Article
- Applied Machine Learning for IIoT and Smart Production-Methods to Improve Production Quality, Safety and Sustainability.Sensors (Basel, Switzerland) · 2022Article
- Precision Enhancement of Wireless Localization System Using Passive DOA Multiple Sensor Network for Moving Target.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Determining the position of ourselves or our assets has always been important to humans. Technology has helped us, from sextants to outdoor global positioning systems, but real-time indoor positioning has been a challenge. Among the various solutions, network-based positioning became an option with the arrival of 5G mobile networks. The new radio technologies, minimized end-to-end latency, specialized control protocols, and booming computation capacities at the network edge offered the opportunity to leverage the overall capabilities of the 5G network for positioning-indoors and outdoors. This paper provides an overview of network-based positioning, from the basics to advanced, state-of-the-art machine-learning-supported solutions. One of the main contributions is the detailed comparison of machine learning techniques used for network-based positioning. Since new requirements are already in place for 6G networks, our paper makes a leap towards positioning with 6G networks. In order to also highlight the practical side of the topic, application examples from different domains are presented with a special focus on industrial and vehicular scenarios.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.