72 citations · 350 across the 20 of their papers we have counts for
10 papers · 1 filter
STR-Agent: An LLM-Driven Agent for QoS-Aware Routing in LEO Satellite Networks
Bowen Lu, Mugen Peng, Yaohua Sun +3
LEO satellite networks feature dynamic topologies, time-varying links, and diverse service requirements, which make conventional routing schemes difficult to support fine-grained q…
Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial
Bisheng Wei, Ruihong Jiang, Ruichen Zhang +9
The rapid advancement toward sixth-generation (6G) wireless networks has significantly intensified the complexity and scale of optimization problems, including resource allocation…
Cache-Aware Cooperative Multicast Beamforming in Dynamic Satellite-Terrestrial Networks
Shuo Yuan, Yaohua Sun, Mugen Peng
With the burgeoning demand for data-intensive services, satellite-terrestrial networks (STNs) face increasing backhaul link congestion, deteriorating user quality of service (QoS),…
Satellite-Terrestrial Integrated Fog Networks: Architecture, Technologies, and Challenges
Shuo Yuan, Mugen Peng, Yaohua Sun
In the evolution of sixth-generation (6G) mobile communication networks, satellite-terrestrial integrated networks emerge as a promising paradigm, characterized by their wide cover…
Distributed Satellite-Terrestrial Cooperative Routing Strategy Based on Minimum Hop-Count Analysis in Mega LEO Satellite Constellation
Xin'ao Feng, Yaohua Sun, Mugen Peng
Mega low earth orbit (LEO) satellite constellation is promising in achieving global coverage with high capacity. However, forwarding packets in mega constellation faces long end-to…
Joint Sensing, Communication, and Computation Resource Allocation for Cooperative Perception in Fog-Based Vehicular Networks
Xinran Zhang, Zhimin He, Yaohua Sun +2
To enlarge the perception range and reliability of individual autonomous vehicles, cooperative perception has been received much attention. However, considering the high volume of…
Mode Selection and Resource Allocation in Sliced Fog Radio Access Networks: A Reinforcement Learning Approach
Hongyu Xiang, Mugen Peng, Yaohua Sun +1
The mode selection and resource allocation in fog radio access networks (F-RANs) have been advocated as key techniques to improve spectral and energy efficiency. In this paper, we…
Deep Reinforcement Learning Based Mode Selection and Resource Allocation for Cellular V2X Communications
Xinran Zhang, Mugen Peng, Shi Yan +1
Cellular vehicle-to-everything (V2X) communication is crucial to support future diverse vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehic…
Deep Reinforcement Learning Based Mode Selection and Resource Management for Green Fog Radio Access Networks
Yaohua Sun, Mugen Peng, Shiwen Mao
Fog radio access networks (F-RANs) are seen as potential architectures to support services of internet of things by leveraging edge caching and edge computing. However, current wor…
Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues
Yaohua Sun, Mugen Peng, Yangcheng Zhou +2
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of solving complex problems without explicit programming. Motivated by its successful appl…