Indoor Positioning Platform to Support 5G Location Based Services

Positioning in general will play an important role in future 5G networks by enabling a vast amount of different location-based services and applications. To offer enriched end-user information and more efficient network performance, location information becomes increasingly more important especially indoors. Therefore, we have designed and implemented an indoor positioning platform to support the development of foreseen location based 5G network functionalities and services. This paper presents the overall system architecture, linkage to the 5G Test Network Finland, and initial trial results with different positioning methods.

[1]  Xuefeng Yin,et al.  Neural-Network-Assisted UE Localization Using Radio-Channel Fingerprints in LTE Networks , 2017, IEEE Access.

[2]  Zhetao Li,et al.  SAP: A Novel Stationary Peers Assisted Indoor Positioning System , 2018, IEEE Access.

[3]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[4]  Haorui Peng,et al.  Research and development of indoor positioning , 2016, China Communications.

[5]  Marco Di Felice,et al.  WI-LO: Wireless indoor localization through multi-source radio fingerprinting , 2018, 2018 10th International Conference on Communication Systems & Networks (COMSNETS).

[6]  Tsung-Nan Lin,et al.  Performance comparison of indoor positioning techniques based on location fingerprinting in wireless networks , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[7]  Katsuyuki Haneda,et al.  Impacts of Room Structure Models on the Accuracy of 60 GHz Indoor Radio Propagation Prediction , 2015, IEEE Antennas and Wireless Propagation Letters.

[8]  S. Lembo,et al.  Indoor Positioning Based on RSS Fingerprinting in a LTE Network: Method Based on Genetic Algorithms , 2019, 2019 IEEE International Conference on Communications Workshops (ICC Workshops).

[9]  Lin Ma,et al.  Geographic information system based estimation and correction algorithm for outdoor location , 2017, 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP).

[10]  Sasu Tarkoma,et al.  A Testbed for LTE-Wi-Fi Indoor and Outdoor Positioning for End-User Localisation , 2017, IPIN 2017.

[11]  Qi Liu,et al.  Research and development of indoor positioning , 2016 .

[12]  Ronald Raulefs,et al.  Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications , 2017, IEEE Communications Surveys & Tutorials.

[13]  Wei Chen,et al.  Knowledge-based error detection and correction method of a Multi-sensor Multi-network positioning platform for pedestrian indoor navigation , 2010, IEEE/ION Position, Location and Navigation Symposium.

[14]  Sangjoon Park,et al.  Towards a Sustainable Open Platform for Location Intelligence and Convergence , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).