collaborators

6 papers

cs.IT2026

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…

cs.IT2025

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…

cs.LG2025

WirelessMathLM: Teaching Mathematical Reasoning for LLMs in Wireless Communications with Reinforcement Learning

Xin Li, Mengbing Liu, Yiyang Zhu +4

Large language models (LLMs) excel at general mathematical reasoning but fail catastrophically on specialized technical mathematics. In wireless communications, where problems requ…

cs.IT2025

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…

eess.SP2025

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…

cs.IT2025

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…