37 citations · 41 across the 13 of their papers we have counts for
11 papers
Distributed On-Device LLM Inference With Over-the-Air Computation
Kai Zhang, Hengtao He, Shenghui Song +2
Large language models (LLMs) have achieved remarkable success across various artificial intelligence tasks. However, their enormous sizes and computational demands pose significant…
Fast Adaptation for Deep Learning-based Wireless Communications
Ouya Wang, Hengtao He, Shenglong Zhou +4
The integration with artificial intelligence (AI) is recognized as one of the six usage scenarios in next-generation wireless communications. However, several critical challenges h…
Distributed Expectation Propagation Detection for Cell-Free Massive MIMO
Hengtao He, Hanqing Wang, Xianghao Yu +3
In cell-free massive MIMO networks, an efficient distributed detection algorithm is of significant importance. In this paper, we propose a distributed expectation propagation (EP)…
Adaptive Channel Estimation Based on Model-Driven Deep Learning for Wideband mmWave Systems
Weijie Jin, Hengtao He, Chao-Kai Wen +2
Channel estimation in wideband millimeter-wave (mmWave) systems is very challenging due to the beam squint effect. To solve the problem, we propose a learnable iterative shrinkage…
Model-Driven Deep Learning for Massive MU-MIMO with Finite-Alphabet Precoding
Hengtao He, Mengjiao Zhang, Shi Jin +2
Massive multiuser multiple-input multiple-output (MU-MIMO) has been the mainstream technology in fifth-generation wireless systems. To reduce high hardware costs and power consumpt…
Model-Driven Deep Learning for MIMO Detection
Hengtao He, Chao-Kai Wen, Shi Jin +1
In this paper, we investigate the model-driven deep learning (DL) for MIMO detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and…