A State-of-the-Art Survey on Multidimensional Scaling Based Localization Techniques
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Abstract (arXiv)
Current and future wireless applications strongly rely on precise real-time localization. A number of applications such as smart cities, Internet of Things (IoT), medical services, automotive industry, underwater exploration, public safety, and military systems require reliable and accurate localization techniques. Generally, the most popular localization/ positioning system is the Global Positioning System (GPS). GPS works well for outdoor environments but fails in indoor and harsh environments. Therefore, a number of other wireless local localization techniques are developed based on terrestrial wireless networks, wireless sensor networks (WSNs) and wireless local area networks (WLANs). Also, there exist localization techniques which fuse two or more technologies to find out the location of the user, also called signal of opportunity based localization. Most of the localization techniques require ranging measurements such as time of arrival (ToA), time difference of arrival (TDoA), direction of arrival (DoA) and received signal strength (RSS). There are also range-free localization techniques which consider the proximity information and do not require the actual ranging measurements. Dimensionality reduction techniques are famous among the range free localization schemes. Multidimensional scaling (MDS) is one of the dimensionality reduction technique which has been used extensively in the recent past for wireless networks localization. In this paper, a comprehensive survey is presented for MDS and MDS based localization techniques in WSNs, Internet of Things (IoT), cognitive radio networks, and 5G networks.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jun 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 0; 2025: 3; 2026: 2.
9 papers.
- 2022Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approachcited by 8
- 2023Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markerscited by 8
- 2023Velocity-Based Channel Charting with Spatial Distribution Map Matchingcited by 5
- 2021A Subspace-based Approach for Dimensionality Reduction and Important Variable Selectioncited by 1
- 2025Learning Isometric Embeddings of Road Networks using Multidimensional Scalingcited by 1
- 2025Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descentcited by 1
- 2025evomap: A Toolbox for Dynamic Mapping in Pythoncited by 0
- 2026OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environmentscited by 0
- 2026Robust conditional dimension reduction for dissimilarity datacited by 0
- 2026Robust conditional dimension reduction for dissimilarity data5 Sep 2026
- 2026OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environments9 Jun 2026
- 2025evomap: A Toolbox for Dynamic Mapping in Python6 Nov 2025
- 2025Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descent28 Apr 2025
- 2025Learning Isometric Embeddings of Road Networks using Multidimensional Scaling24 Apr 2025
- 2023Velocity-Based Channel Charting with Spatial Distribution Map Matching14 Nov 2023
- 2023Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers25 Oct 2023
- 2022Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach7 Oct 2022
- 2021A Subspace-based Approach for Dimensionality Reduction and Important Variable Selection3 Jun 2021