9 papers · 1 filter
Heterogeneous Multi-Agent Reinforcement Learning for Distributed Channel Access in WLANs
Jiaming Yu, Le Liang, Chongtao Guo +3
This paper investigates the use of multi-agent reinforcement learning (MARL) to address distributed channel access in wireless local area networks. In particular, we consider the c…
ISAC Prototype System for Multi-Domain Cooperative Communication Networks
Jie Yang, Hang Que, Tao Du +4
Future wireless networks are poised to transform into integrated sensing and communication (ISAC) networks, unlocking groundbreaking services such as digital twinning. To harness t…
Semantic Communication for Cooperative Perception using HARQ
Yucheng Sheng, Le Liang, Hao Ye +2
Cooperative perception, offering a wider field of view than standalone perception, is becoming increasingly crucial in autonomous driving. This perception is enabled through vehicl…
GRLinQ: An Intelligent Spectrum Sharing Mechanism for Device-to-Device Communications with Graph Reinforcement Learning
Zhiwei Shan, Xinping Yi, Le Liang +2
Device-to-device (D2D) spectrum sharing in wireless communications is a challenging non-convex combinatorial optimization problem, involving entangled link scheduling and power con…
Generative Diffusion Models for High Dimensional Channel Estimation
Xingyu Zhou, Le Liang, Jing Zhang +3
Along with the prosperity of generative artificial intelligence (AI), its potential for solving conventional challenges in wireless communications has also surfaced. Inspired by th…
Beam Prediction based on Large Language Models
Yucheng Sheng, Kai Huang, Le Liang +3
In this letter, we use large language models (LLMs) to develop a high-performing and robust beam prediction method. We formulate the millimeter wave (mmWave) beam prediction proble…
Mini-Batch Gradient-Based MCMC for Decentralized Massive MIMO Detection
Xingyu Zhou, Le Liang, Jing Zhang +2
Massive multiple-input multiple-output (MIMO) technology has significantly enhanced spectral and power efficiency in cellular communications and is expected to further evolve towar…
Near-Optimal MIMO Detection Using Gradient-Based MCMC in Discrete Spaces
Xingyu Zhou, Le Liang, Jing Zhang +2
The discrete nature of transmitted symbols poses challenges for achieving optimal detection in multiple-input multiple-output (MIMO) systems associated with a large number of anten…
On Purely Data-Driven Massive MIMO Detectors
Hao Ye, Le Liang
The development of learning-based detectors for massive multi-input multi-output (MIMO) systems has been hindered by the inherent complexities arising from the problem's high dimen…