146 citations · 641 across the 84 of their papers we have counts for
20 papers · 1 filter
NetWorld: Communication-Based Diffusion World Model for Multi-Agent Reinforcement Learning in Wireless Networks
Kechen Meng, Rongpeng Li, Yansha Deng +2
As wireless communication networks grow in scale and complexity, diverse resource allocation tasks become increasingly critical. Multi-Agent Reinforcement Learning (MARL) provides…
Optimizing NetGPT via Routing-Based Synergy and Reinforcement Learning
Yuxuan Chen, Rongpeng Li, Xianfu Chen +4
Large language model (LLM) agents at the network edge offer low-latency execution for routine queries. In contrast, complex requests often require the superior capability of cloud…
Conditional Diffusion Model with OOD Mitigation as High-Dimensional Offline Resource Allocation Planner in Clustered Ad Hoc Networks
Kechen Meng, Sinuo Zhang, Rongpeng Li +3
Due to network delays and scalability limitations, clustered ad hoc networks widely adopt Reinforcement Learning (RL) for on-demand resource allocation. Albeit its demonstrated agi…
LLM4MAC: An LLM-Driven Reinforcement Learning Framework for MAC Protocol Emergence
Renxuan Tan, Rongpeng Li, Zhifeng Zhao
With the advent of 6G systems, emerging hyper-connected ecosystems necessitate agile and adaptive medium access control (MAC) protocols to contend with network dynamics and diverse…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G
Xiaoxue Yu, Xingfu Yi, Rongpeng Li +4
In the evolution towards 6G, integrating Artificial Intelligence (AI) with advanced network infrastructure emerges as a pivotal strategy for enhancing network intelligence and reso…
Ten issues of NetGPT
Wen Tong, Chenghui Peng, Tingting Yang +15
With the rapid development and application of foundation models (FMs), it is foreseeable that FMs will play an important role in future wireless communications. As current Artifici…
RHFedMTL: Resource-Aware Hierarchical Federated Multi-Task Learning
Xingfu Yi, Rongpeng Li, Chenghui Peng +3
The rapid development of artificial intelligence (AI) over massive applications including Internet-of-things on cellular network raises the concern of technical challenges such as…
Toward Native Artificial Intelligence in 6G Networks: System Design, Architectures, and Paradigms
Jianjun Wu, Rongpeng Li, Xueli An +4
The mobile communication system has transformed to be the fundamental infrastructure to support digital demands from all industry sectors, and 6G is envisioned to go far beyond the…
Fundamentals on Base Stations in Cellular Networks: From the Perspective of Algebraic Topology
Ying Chen, Rongpeng Li, Zhifeng Zhao +1
In recent decades, the deployments of cellular networks have been going through an unprecedented expansion. In this regard, it is beneficial to acquire profound knowledge of cellul…
Study on Base Station Topology in Cellular Networks: Take Advantage of Alpha Shapes, Betti Numbers, and Euler Characteristics
Ying Chen, Rongpeng Li, Zhifeng Zhao +1
Faced with the ever-increasing trend of the cellular network scale, how to quantitatively evaluate the effectiveness of the large-scale deployment of base stations (BSs) has become…
Deep Reinforcement Learning for Resource Management in Network Slicing
Rongpeng Li, Zhifeng Zhao, Qi Sun +5
Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices. In order to provide better-perf…
Effect of Spatial and Temporal Traffic Statistics on the Performance of Wireless Networks
Gang Wang, Yi Zhong, Rongpeng Li +3
The traffic in wireless networks has become diverse and fluctuating both spatially and temporally due to the emergence of new wireless applications and the complexity of scenarios.…
Traffic Prediction Based on Random Connectivity in Deep Learning with Long Short-Term Memory
Yuxiu Hua, Zhifeng Zhao, Rongpeng Li +3
Traffic prediction plays an important role in evaluating the performance of telecommunication networks and attracts intense research interests. A significant number of algorithms a…
The Learning and Prediction of Application-level Traffic Data in Cellular Networks
Rongpeng Li, Zhifeng Zhao, Jianchao Zheng +3
Traffic learning and prediction is at the heart of the evaluation of the performance of telecommunications networks and attracts a lot of attention in wired broadband networks. Now…
On the Limits of Predictability in Real-World Radio Spectrum State Dynamics: From Entropy Theory to 5G Spectrum Sharing
Guoru Ding, Jinlong Wang, Qihui Wu +4
A range of applications in cognitive radio networks, from adaptive spectrum sensing to predictive spectrum mobility and dynamic spectrum access, depend on our ability to foresee th…
Large-scale Spatial Distribution Identification of Base Stations in Cellular Networks
Yifan Zhou, Zhifeng Zhao, Qianlan Ying +4
The performance of cellular system significantly depends on its network topology, where the spatial deployment of base stations (BSs) plays a key role in the downlink scenario. Mor…
Characterizing Spatial Patterns of Base Stations in Cellular Networks
Qianlan Ying, Zhifeng Zhao, Yifan Zhou +3
The topology of base stations (BSs) in cellular networks, serving as a basis of networking performance analysis, is considered to be obviously distinctive with the traditional hexa…
Two-tier Spatial Modeling of Base Stations in Cellular Networks
Yifan Zhou, Zhifeng Zhao, Qianlan Ying +3
Poisson Point Process (PPP) has been widely adopted as an efficient model for the spatial distribution of base stations (BSs) in cellular networks. However, real BSs deployment are…
TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks
Rongpeng Li, Zhifeng Zhao, Xianfu Chen +2
Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs). In this…