37 citations · 40 across the 8 of their papers we have counts for
9 papers
RadioKMoE: Knowledge-Guided Radiomap Estimation with Kolmogorov-Arnold Networks and Mixture-of-Experts
Fupei Guo, Kerry Pan, Songyang Zhang +2
Radiomap serves as a vital tool for wireless network management and deployment by providing powerful spatial knowledge of signal propagation and coverage. However, increasingly com…
TACO: Rethinking Semantic Communications with Task Adaptation and Context Embedding
Achintha Wijesinghe, Weiwei Wang, Suchinthaka Wanninayaka +2
Recent advancements in generative artificial intelligence have introduced groundbreaking approaches to innovating next-generation semantic communication, which prioritizes conveyin…
Task-Adaptive Semantic Communications with Controllable Diffusion-based Data Regeneration
Fupei Guo, Achintha Wijesinghe, Songyang Zhang +1
Semantic communications represent a new paradigm of next-generation networking that shifts bit-wise data delivery to conveying the semantic meanings for bandwidth efficiency. To ef…
Task-Driven Semantic Quantization and Imitation Learning for Goal-Oriented Communications
Yu-Chieh Chao, Yubei Chen, Weiwei Wang +4
Semantic communication marks a new paradigm shift from bit-wise data transmission to semantic information delivery for the purpose of bandwidth reduction. To more effectively carry…
LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency
Achintha Wijesinghe, Suchinthaka Wanninayaka, Weiwei Wang +3
The recent rise of semantic-style communications includes the development of goal-oriented communications (GOCOMs) remarkably efficient multimedia information transmissions. The co…
Diff-GO: Enhancing Diffusion Models for Goal-Oriented Communications
Suchinthaka Wanninayaka, Achintha Wijesinghe, Weiwei Wang +3
The rapid expansion of edge devices and Internet-of-Things (IoT) continues to heighten the demand for data transport under limited spectrum resources. The goal-oriented communicati…
TiRE-GAN: Task-Incentivized Generative Learning for Radiomap Estimation
Yueling Zhou, Achintha Wijesinghe, Yibo Ma +2
To characterize radio frequency (RF) signal power distribution in wireless communication systems, the radiomap is a useful tool for resource allocation and network management. Usua…
RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networks
Xiaojie Li, Songyang Zhang, Hang Li +7
Multi-band radiomap reconstruction (MB-RMR) is a key component in wireless communications for tasks such as spectrum management and network planning. However, traditional machine-l…
Diff-GO: Diffusion Goal-Oriented Communications to Achieve Ultra-High Spectrum Efficiency
Achintha Wijesinghe, Songyang Zhang, Suchinthaka Wanninayaka +2
The latest advances in artificial intelligence (AI) present many unprecedented opportunities to achieve much improved bandwidth saving in communications. Unlike conventional commun…