11 citations · 13 across the 14 of their papers we have counts for
16 papers
Space AI Infrastructure: Where the Edge Meets the Orbital Cloud
Zhanwei Wang, Jianhao Huang, Min Sheng +1
The fusion of artificial intelligence (AI) and space technologies is extending spaceborne intelligence beyond onboard payloads toward a global infrastructure, here termed Space AI…
SpaceDiffusion: Over-the-Orbit Diffusion for Space Generate-and-Forward Communications
Jianhao Huang, Zhanwei Wang, Khaled B. Letaief +1
Satellite communications are an essential component of sixth-generation (6G) mobile networks, which provide ubiquitous connectivity for global services. However, the satellite upli…
Space Generative AI with Solar Energy Harvesting
Jierui Zhang, Jianhao Huang, Zhanwei Wang +1
Satellites are emerging as promising platforms to extend generative \emph{artificial intelligence} (AI) services to remote areas lacking terrestrial infrastructure. However, deploy…
AirMoE: Realizing Over-the-Air Distributed Mixture-of-Experts Inference at the Wireless Edge
Huiling Yang, Zhanwei Wang, Kaibin Huang
Mixture-of-experts (MoE) architectures enable efficient large language model (LLM) inference at the wireless edge through sparse activation. The wireless distributed MoE (WIDE) arc…
Multi-SPIN: Multi-Access Speculative Inference for Cooperative Token Generation at the Edge
Haotian Zheng, Zhanwei Wang, Mingyao Cui +3
Speculative inference (SPIN) was originally developed as an efficient architecture to accelerate Large Language Models (LLMs). In this work, we propose its distributed deployment t…
SpaceMoE: Realizing Distributed Mixture-of-Experts Inference over Space Networks
Zhanwei Wang, Huiling Yang, Min Sheng +2
Leveraging continuous solar energy harvesting at high efficiency, space data centers are envisioned as a promising platform for executing energy-intensive large language models (LL…
AirBreath Sensing: Protecting Over-the-Air Distributed Sensing Against Interference
Zhanwei Wang, Mingyao Cui, Huiling Yang +3
A distinctive function of sixth-generation (6G) networks is the integration of distributed sensing and edge artificial intelligence (AI) to enable intelligent perception of the phy…
Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity
Huiling Yang, Zhanwei Wang, Kaibin Huang
Federated learning (FL) has emerged as a popular approach for collaborative machine learning in sixth-generation (6G) networks, primarily due to its privacy-preserving capabilities…
Rydberg Atomic Receivers for Multi-Band Communications and Sensing
Mingyao Cui, Qunsong Zeng, Minze Chen +4
Harnessing multi-level electron transitions, Rydberg Atomic REceivers (RAREs) can detect wireless signals across a wide range of frequency bands, from Megahertz to Terahertz. This…
Realizing Quantum Wireless Sensing Without Extra Reference Sources: Architecture, Algorithm, and Sensitivity Maximization
Mingyao Cui, Qunsong Zeng, Zhanwei Wang +1
Rydberg Atomic REceivers (RAREs) have demonstrated remarkable capabilities for radio-frequency signal measurement, enabling advanced quantum wireless sensing. Existing RARE-based s…
Revisiting Outage for Edge Inference Systems
Zhanwei Wang, Qunsong Zeng, Haotian Zheng +1
One of the key missions of sixth-generation (6G) mobile networks is to deploy large-scale artificial intelligence (AI) models at the network edge to provide remote-inference servic…
Ultra-Low-Latency Edge Intelligent Sensing: A Source-Channel Tradeoff and Its Application to Coding Rate Adaptation
Qunsong Zeng, Jianhao Huang, Zhanwei Wang +2
The forthcoming sixth-generation (6G) mobile network is set to merge edge artificial intelligence (AI) and integrated sensing and communication (ISAC) extensively, giving rise to t…
Integrated Sensing and Edge AI: Realizing Intelligent Perception in 6G
Zhiyan Liu, Xu Chen, Hai Wu +4
Sensing and edge artificial intelligence (AI) are envisioned as two essential and interconnected functions in sixth-generation (6G) mobile networks. On the one hand, sensing-empowe…
Space-ground Fluid AI for 6G Edge Intelligence
Qian Chen, Zhanwei Wang, Xianhao Chen +5
Edge artificial intelligence (AI) and space-ground integrated networks (SGINs) are two main usage scenarios of the sixth-generation (6G) mobile networks. Edge AI supports pervasive…
Knowledge-Based Ultra-Low-Latency Semantic Communications for Robotic Edge Intelligence
Qunsong Zeng, Zhanwei Wang, You Zhou +3
The 6G mobile networks will feature the widespread deployment of AI algorithms at the network edge, which provides a platform for supporting robotic edge intelligence systems. In s…
Ultra-Low-Latency Edge Inference for Distributed Sensing
Zhanwei Wang, Anders E. Kalør, You Zhou +2
There is a broad consensus that artificial intelligence (AI) will be a defining component of the sixth-generation (6G) networks. As a specific instance, AI-empowered sensing will g…