A Deep Generative Model for Synthesizing Labeled Wireless Signals
[Sztuczna inteligencja] Autorzy: Yuxiao Li, Keke Hu, Santiago Mazuelas i 1 więcej
Wireless signals with position-related labels are pivotal for both performance evaluation and model training in the realm of wireless sensing. However, acquiring real-world datasets is often challenged by significant measurement and labeling costs. Traditional methods for synthesizing labeled wireless signals typically rely on environmental models, leading to extensive hyper-parameter tuning and inadequate realism for comprehensive model training purposes. To address these limitations, we introduce a novel deep learning (DL)-based method, namely Inter-Instance Generative Adversarial Networks (IIns-GAN), to generate realistic labeled wireless signals. The generated signals are particularly adaptive to different environment scenarios and well-suited for various model training tasks, including distance estimation and environment identification. We have conducted extensive experiments on pu…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja