34 citations · 34 across the 12 of their papers we have counts for
13 papers
Low-Complexity Multi-Agent Continual Learning for Stacked Intelligent Metasurface-Assisted Secure Communications
Enyu Shi, Yiyang Zhu, Jiayi Zhang +6
Stacked intelligent metasurfaces (SIMs), composed of multiple layers of reconfigurable transmissive metasurfaces, are gaining prominence as a transformative technology for future w…
WirelessMathBench-XL: An Auditable Benchmark for Wireless Mathematical Reasoning
Xin Li, Mengbing Liu, Yiyang Zhu +4
Benchmarks built from arXiv papers can overlap the arXiv text used in LLM pretraining, yet technical-domain releases rarely ship the per-item evidence needed to check this. We intr…
Beamforming Design for Beyond Diagonal RIS-Aided Cell-Free Massive MIMO Systems
Yizhuo Li, Jiakang Zheng, Bokai Xu +4
Reconfigurable intelligent surface (RIS)-aided cell-free (CF) massive multiple-input multiple-output (mMIMO) is a promising technology for further improving spectral efficiency (SE…
Joint Power Allocation and Phase Shift Design for Stacked Intelligent Metasurfaces-aided Cell-Free Massive MIMO Systems with MARL
Yiyang Zhu, Jiayi Zhang, Enyu Shi +3
Cell-free (CF) massive multiple-input multiple-output (mMIMO) systems offer high spectral efficiency (SE) through multiple distributed access points (APs). However, the large numbe…
Robust Multidimensional Graph Neural Networks for Signal Processing in Wireless Communications with Edge-Graph Information Bottleneck
Ziheng Liu, Jiayi Zhang, Yiyang Zhu +2
Signal processing is crucial for satisfying the high data rate requirements of future sixth-generation (6G) wireless networks. However, the rapid growth of wireless networks has br…
Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G
Jiayi Zhang, Ziheng Liu, Yiyang Zhu +9
The introduction of intelligent interconnectivity between the physical and human worlds has attracted great attention for future sixth-generation (6G) networks, emphasizing massive…
Mobile Cell-Free Massive MIMO with Multi-Agent Reinforcement Learning: A Scalable Framework
Ziheng Liu, Jiayi Zhang, Yiyang Zhu +2
Cell-free massive multiple-input multiple-output (mMIMO) offers significant advantages in mobility scenarios, mainly due to the elimination of cell boundaries and strong macro dive…
Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning
Enyu Shi, Jiayi Zhang, Ziheng Liu +5
Cell-free (CF) massive multiple-input multiple-output (mMIMO) and reconfigurable intelligent surface (RIS) are two advanced transceiver technologies for realizing future sixth-gene…
Cooperative Multi-Target Positioning for Cell-Free Massive MIMO with Multi-Agent Reinforcement Learning
Ziheng Liu, Jiayi Zhang, Enyu Shi +3
Cell-free massive multiple-input multiple-output (mMIMO) is a promising technology to empower next-generation mobile communication networks. In this paper, to address the computati…
Distributed Collaborative User Positioning for Cell-Free Massive MIMO with Multi-Agent Reinforcement Learning
Ziheng Liu, Jiayi Zhang, Enyu Shi +3
In this paper, we investigate a cell-free massive multiple-input multiple-output system, which exhibits great potential in enhancing the capabilities of next-generation mobile comm…
Harnessing Stacked Intelligent Metasurface for Enhanced Cell-Free Massive MIMO Systems: A Low-Power and Cost Approach
Enyu Shi, Jiayi Zhang, Yiyang Zhu +3
In this paper, we explore the integration of low-power, low-cost stacked intelligent metasurfaces (SIM) into cell-free (CF) massive multiple-input multiple-output (mMIMO) systems t…
Performance Analysis of RIS-aided MISO Systems with EMI and Channel Aging
Taoyu Song, Enyu Shi, Yu Lu +3
In this paper, we investigate a reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) system in the presence of electromagnetic interference (EMI) and…
Multi-agent Reinforcement Learning-based Joint Precoding and Phase Shift Optimization for RIS-aided Cell-Free Massive MIMO Systems
Yiyang Zhu, Enyu Shi, Ziheng Liu +2
Cell-free (CF) massive multiple-input multiple-output (mMIMO) is a promising technique for achieving high spectral efficiency (SE) using multiple distributed access points (APs). H…