Adaptive detection probability for mmWave 5G SLAM
Paper in proceedings, 2020

In 5G simultaneous localization and mapping (SLAM), estimates of angles and delays of mm Wave channels are used to localize the user equipment and map the environment. The interface from the channel estimator to the SLAM method, which was previously limited to the channel parameters estimates and their uncertainties, is here augmented to include the detection probabilities of hypothesized landmarks, given certain a user location. These detection probabilities are used during data association and measurement update, which are important steps in any SLAM method. Due to the nature of mm Wave communication, these detection probabilities depend on the physical layer signal parameters, including beamforming, precoding, bandwidth, observation time, etc. In this paper, we derive these detection probabilities for different deterministic and stochastic channel models and highlight the importance of beamforming.

Author

Henk Wymeersch

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

G. Seco-Granados

Universitat Autonoma de Barcelona (UAB)

2nd 6G Wireless Summit 2020: Gain Edge for the 6G Era, 6G SUMMIT 2020

9083898

2nd 6G Wireless Summit, 6G SUMMIT 2020
Levi, Lapland, Finland,

Multi-dimensional Signal Processing with Frequency Comb Transceivers

Swedish Research Council (VR), 2018-12-01 -- 2021-12-31.

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1109/6GSUMMIT49458.2020.9083898

More information

Latest update

1/14/2021