Data-Importance-Aware Power Allocation for Adaptive Real-Time Communication in Computer Vision Applications

no code implementations • 11 Apr 2025 • Chunmei Xu, Yi Ma, Rahim Tafazolli, Jiangzhou Wang

To minimize IMSE under total power constraints, data-importance-aware waterfilling approaches are proposed to optimally allocate transmission power according to data importance and channel conditions, prioritizing sub-streams with high importance.

Data-Importance-Aware Waterfilling for Adaptive Real-Time Communication in Computer Vision Applications

no code implementations • 28 Feb 2025 • Chunmei Xu, Yi Ma, Rahim Tafazolli

This paper presents a novel framework for importance-aware adaptive data transmission, designed specifically for real-time computer vision (CV) applications where task-specific fidelity is critical.

Importance-Aware Source-Channel Coding for Multi-Modal Task-Oriented Semantic Communication

no code implementations • 22 Feb 2025 • Yi Ma, Chunmei Xu, Zhenyu Liu, Siqi Zhang, Rahim Tafazolli

This paper explores the concept of information importance in multi-modal task-oriented semantic communication systems, emphasizing the need for high accuracy and efficiency to fulfill task-specific objectives.

Semantic Communication

Generative Semantic Communications with Foundation Models: Perception-Error Analysis and Semantic-Aware Power Allocation

no code implementations • 7 Nov 2024 • Chunmei Xu, Mahdi Boloursaz Mashhadi, Yi Ma, Rahim Tafazolli, Jiangzhou Wang

Generative foundation models can revolutionize the design of semantic communication (SemCom) systems allowing high fidelity exchange of semantic information at ultra low rates.

Decoder Semantic Communication

Semantic-Aware Power Allocation for Generative Semantic Communications with Foundation Models

no code implementations • 3 Jul 2024 • Chunmei Xu, Mahdi Boloursaz Mashhadi, Yi Ma, Rahim Tafazolli

Recent advancements in diffusion models have made a significant breakthrough in generative modeling.

Semantic Communication

Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks

no code implementations • 20 Feb 2024 • Chunmei Xu, Shengheng Liu, Yongming Huang, Bjorn Ottersten, Dusit Niyato

Extensive simulation results are presented to demonstrate the effectiveness of the proposed random aggregate beamforming-based scheme as well as the refined method.

Federated Learning

Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions

no code implementations • 2 Nov 2022 • Senthil Kumar Jagatheesaperumal, Quoc-Viet Pham, Rukhsana Ruby, Zhaohui Yang, Chunmei Xu, Zhaoyang Zhang

Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)