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Wireless localization for mmWave networks in urban environments.
1Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC US.
EURASIP Journal on Advances in Signal Processing
|April 19, 2019
Summary
Millimeter wave (mmWave) localization enhances 5G networks by accurately pinpointing user equipment (UE) locations. A novel gradient-assisted particle filter (GAPF) estimator improves accuracy, even in complex urban environments with radio-environmental mapping (REM).
Area of Science:
- Wireless Communications
- Signal Processing
- Localization Technologies
Background:
- Millimeter wave (mmWave) technology is crucial for 5G wireless networks, offering ultra-wide bandwidths.
- mmWave systems enable precise multipath component identification, benefiting localization applications.
- Accurate localization in urban environments with line-of-sight (LOS) and non-LOS (NLOS) links presents significant challenges.
Purpose of the Study:
- To analyze a two-step mmWave localization approach using time-of-arrival, angle-of-arrival, and angle-of-departure.
- To address challenges in user equipment (UE) location estimation caused by multiple local optima.
- To propose and evaluate a gradient-assisted particle filter (GAPF) estimator for UE and scatterer localization.
Main Methods:
- Utilized time-of-arrival, angle-of-arrival, and angle-of-departure from multiple nodes.
- Implemented a two-step localization approach in urban environments with and without radio-environmental mapping (REM).
- Developed a gradient-assisted particle filter (GAPF) estimator to overcome localization challenges.
Main Results:
- The GAPF estimator accurately estimates UE and nearby scatterer locations.
- Monte-Carlo simulations demonstrate GAPF performance matching the Cramer-Rao bound (CRB).
- Radio-environmental mapping (REM) and increased beam directionality significantly improve localization gains.
Conclusions:
- The proposed GAPF estimator effectively addresses UE localization challenges in mmWave systems.
- The study validates the benefits of REM and beam directionality for enhanced localization accuracy.
- mmWave technology, coupled with advanced estimation techniques, shows great promise for future 5G localization services.
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