SymNetPro: LOS-Aware Directional Multi-Transmitter Localization from Sparse Radio Observations
Abstract
Directional multi-transmitter localization from sparse received-power observations is difficult because the receiver observes only the source-unresolved aggregate field: multiple directional sources superpose, building blockage fragments their visible regions, and stronger sources can mask weaker ones. We present SymNetPro, which retains the dual-task radio-map reconstruction and localization backbone of SymNet and adds two targeted components. First, a sparse line-of-sight (LOS)-aware attention bias injects obstruction-aware spatial relations into selected token interactions. Second, transmitter-drop augmentation recomposes training scenes after removing one sample-supported transmitter, exposing the model to controlled source-cardinality variation. Experiments on directional ray-traced urban environments show substantially lower OSPA than representative localization baselines under extreme sparse sampling, with consistent gains under measurement noise and increasing transmitter count. A transmitter-specific evidence analysis further shows that remaining misses concentrate in regimes where the target contributes little distinguishable power to the aggregate observation.
Related
- The directional localization game on graphs
- Data Assimilation with Sparse Observations
- Recovering linear images of sparse signals from indirect observations
- Off-Grid Point-Scatterer Localization from Sparse Limited-Aperture Data via Hankel Completion
- Instance Optimal Sparse Recovery from Nonlinear Observations: A Unified Framework
BibTeX
@misc{ye2026symnetpro,
title = {{SymNetPro: LOS-Aware Directional Multi-Transmitter Localization from Sparse Radio Observations}},
author = {Lyuzhou Ye and Heng Fan and Yan Huang},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.33964},
eprint = {2609.33964},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.33964},
}
RIS
TY - UNPB
TI - SymNetPro: LOS-Aware Directional Multi-Transmitter Localization from Sparse Radio Observations
AU - Lyuzhou Ye
AU - Heng Fan
AU - Yan Huang
PY - 2026
DA - 2026/10/06
PB - arXiv
DO - 10.48550/arxiv.2609.33964
UR - https://arxiv.org/abs/2609.33964
AB - Directional multi-transmitter localization from sparse received-power observations is difficult because the receiver observes only the source-unresolved aggregate field: multiple directional sources superpose, building blockage fragments their visible regions, and stronger sources can mask weaker ones. We present SymNetPro, which retains the dual-task radio-map reconstruction and localization backbone of SymNet and adds two targeted components. First, a sparse line-of-sight (LOS)-aware attention bias injects obstruction-aware spatial relations into selected token interactions. Second, transmitter-drop augmentation recomposes training scenes after removing one sample-supported transmitter, exposing the model to controlled source-cardinality variation. Experiments on directional ray-traced urban environments show substantially lower OSPA than representative localization baselines under extreme sparse sampling, with consistent gains under measurement noise and increasing transmitter count. A transmitter-specific evidence analysis further shows that remaining misses concentrate in regimes where the target contributes little distinguishable power to the aggregate observation.
ER -