Call for Participation
In urban environments, Global Navigation Satellite Systems fail to provide good accuracy because of the low likelihood of line-of-sight (LOS) links between the User Equipment (UE) to be located and the satellites, due to the presence the buildings that block the satellite signals. Thus, other approaches, that can reliably operate under non-line-of-sight (NLOS) conditions are required.
In the recent years, many researchers have developed algorithms that are tailored to perform under heavy NLOS conditions. Many of such methods use Received Signal Strength (RSS) or Time of Arrival (ToA) (or both, in hybrid methods) information regarding the beacon signals that are regularly sent from wireless anchor infrastructure nodes such as Base Stations (BS) or Access Points (AP).
In order to foster research and facilitate fair comparisons among the methods in realistic NLOS heavy conditions, we provide a pathloss radio map dataset based on accurate radio wave propagation simulations along with the corresponding novel ToA radio map dataset generated under realistic urban scenarios and launch the Urban Wireless Localization Competition.
The main task of the competition is to develop highly accurate localization methods which can make use of RSS (pathloss) and ToA measurements.
The ranking of the methods is going to be based on the average of their accuracies in NLOS-only and NLOS/LOS-mixed scenarios and under different noise levels on the RSS and ToA measurements.
The top 3 ranked teams will be invited to submit a (maximum) 6-page paper and present it at MLSP 2023. The accepted papers will be published in the MLSP proceedings.
The deadline for the submission of the results (location estimates in the test set), trained models (if applicable), and the test codes is July 12, 2023.
The registraion closes on July 1, 2023.
Support on the dataset and the instructions will be provided by the organizing team.
IMPORTANT NOTE: The intellectual property (IP) of the shared/submitted material (e.g. code) will not be transferred to the challenge organizers. When such material is made publicly available by a participant, an appropriate license should accompany.
Main Task: Location Estimation using RSS/ToA
The main task of the challenge is to achieve accurate location estimates by using either or both the pathloss and ToA radio maps.
The participants are asked to develop methods that are robust to realistic inaccuracies in their radio map estimates. To this end, we model the mismatch between the available and real RSS and ToA information by additive Gaussian noise terms.
The ranking of the submitted methods will be based on the average of their accuracies in NLOS-only and NLOS/LOS-mixed scenarios and under different noise levels on the RSS and ToA measurements (the exact values of the noise variances to be decided).
Optional Tasks: RSS- or ToA-only localization
The participants are encouraged to also submit methods that only use the RSS or ToA information.