Huawei Launches First Industry-Oriented 5G Indoor Positioning Solution
At the 19th Huawei Global Analyst Summit (HAS 2022) held on Tuesday, leading Chinese telecommunications firm Huawei released the industry’s first business-used solution regarding 5G indoor positioning.
This technology solves many engineering problems such as difficult positioning under complex scenarios and the increase of beacons. The positioning offered by this solution is accurate to 1-3 meters at 90%, while supporting open standard interface for industry applications. This solution allows enterprises to implement reliable, secure, and differentiated E2E 5G positioning within their campuses.
5G positioning was introduced through 3GPP Release 16, with a designed accuracy of 3 meters at 80% indoors. The President of Huawei’s DIS Product Line, Marvin Chen, said: “Huawei has verified 5G indoor positioning in many industries, like manufacturing, warehousing, and transportation. The verification showed that the positioning accuracy reached 1-3 meters at 90% in line of sight (LOS) indoors. Exceeding the 3GPP requirements, such a high level of positioning accuracy allows most business applications to adequately locate personnel, equipment, and materials. The company is now working to increase the accuracy to within 1 meter to fulfill advanced 3GPP requirements.”
Huawei’s 5G indoor positioning solution includes wireless LampSite Enterprise Edition (EE) and on-premises Location Service (LCS) modules. It supports LCS open standard interface for third-party positioning platforms and applications that need location services.
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This solution provides three positioning technologies including “uplink time difference of arrival” (UTDOA), wireless fingerprint and field strength to ensure indoor positioning can be implemented in both LOS and non-light-of-sight (NLOS) environments.
Huawei has realized automatic fingerprint library generation and UTDOA-needed beacon-free correction of signal arrival time differences by using “radio simultaneous localization and mapping” (Radio SLAM) and AI-based big data clustering iteration algorithms. Therefore, these two promotional problems, including the collection of fingerprints and beacon placement, can be settled.