559 citations · 606 across the 5 of their papers we have counts for
6 papers
FBOS-RL: Feedback-Driven Bi-Objective Synergistic Reinforcement Learning
Xikai Zhang, Yongzhi Li, Likang Xiao +6
Reinforcement learning has become a cornerstone for aligning and unlocking the reasoning capabilities of large-scale models. At its core, the training loop of GRPO and its variants…
IMAGINE: Integrating Multi-Agent System into One Model for Complex Reasoning and Planning
Xikai Zhang, Bo Wang, Likang Xiao +4
Although large language models (LLMs) have made significant strides across various tasks, they still face significant challenges in complex reasoning and planning. For example, eve…
Optimal Design of Energy and Spectral Efficiency Tradeoff in One-Bit Massive MIMO Systems
Yongzhi Li, Cheng Tao, Amine Mezghani +3
This paper considers a single-cell massive multiple-input multiple-output (MIMO) system equipped with a base station (BS) that uses one-bit quantization and investigates the energy…
Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems
Yongzhi Li, Cheng Tao, Gonzalo Seco-Granados +3
This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output (MIMO) system. Each receive antenna of the bas…
How Much Training is Needed in One-Bit Massive MIMO Systems at Low SNR?
Yongzhi Li, Cheng Tao, Liu Liu +2
This paper considers training-based transmissions in massive multi-input multi-output (MIMO) systems with one-bit analog-to-digital converters (ADCs). We assume that each coherent…
Channel Estimation and Uplink Achievable Rates in One-Bit Massive MIMO Systems
Yongzhi Li, Cheng Tao, Liu Liu +2
This paper considers channel estimation and achievable rates for the uplink of a massive multiple-input multiple-output (MIMO) system where the base station is equipped with one-bi…