Telefonaktiebolaget Lm Ericsson (publ)

Yang Zhang

Oskar Mauritz

Di Shu

Torbjörn Wigren

Edison Shu

Aron Yu

There is provided mechanisms for determining time-of-arrival of a PRACH preamble. A method is performed by a radio access network node. The radio access network node is configured for beamformed communication in a set of beams. The method comprises receiving, from a UE and at a TRP of the radio access network node, a PRACH preamble. The method comprises determining a weight factor value for the PRACH preamble. The weight factor value is dependent on beam information mapped to the PRACH preamble. The beam information identifies one of the beams in the set of beams. The method comprises determining time-of-arrival of the PRACH preamble using hypothesis testing that incorporates the weight factor value.

Time-of-arrival determination of a PRACH preamble

Random access preamble detection for propagation delay is described herein. The proposed solution predicts energy levels for a set of hypotheses, compares the predicted energy with measured energy, and selects the hypothesis that minimizes a cost function based on the difference of the predicted energy and the measured energy. Some embodiments of the proposed solution may make it possible to extend cell range by allowing a maximum round-trip time exceeding the period of the random access preamble sequence. For the long preamble formats for Long Term Evolution (LTE) and New Radio (NR), the cell range may be extended beyond 120 kilometers (km). For millimeter wave applications, the cell range may be extended beyond 2.5 km.

Random access preamble detection for propagation delay

Machine-to-machine (M2M) devices are used to enable the automatic collection of fingerprint data without human intervention at various locations in a wireless communication system. A location server receives fingerprint data collected by one or more M2M devices positioned at fixed locations in the wireless communication system, and stores the fingerprint data received for each of the one or more M2M devices in the location database to associate the received fingerprint data with the fixed location of the corresponding M2M device. The collected fingerprint data characterizes the radio environment at the fixed location of the corresponding M2M device, where each M2M device corresponds to one fixed location in a fingerprint grid.

Location positioning using M2M ecosystem

Presented are methods and apparatus for generating an inaccuracy characteristic for a fingerprinting positioning algorithm calculation associated with a user equipment location. Fingerprinting positioning measurements are compared to high-accuracy positioning measurements and an error value is determined. The error values are accumulated and the inaccuracy characteristic is generated based on an inaccuracy calculation. For areas where insufficient data is available, an inaccuracy characteristic value can be interpolated or extrapolated from adjacent areas containing sufficient data.

Wireless communication network for estimating the accuracy of fingerprinting positioning algorithms

A method of determining geographic position of mobile terminals in a mobile communication network comprises receiving raw measurement data in the mobile communication network, adapting the raw measurement data to be stored in an image format, and determining geographic position of mobile terminals based on the raw measurement data stored in the image format.

Growing community of inventors

Sollentuna, Sweden

Yang Zhang