1 citations · 1 across the 4 of their papers we have counts for
4 papers
Model-driven deep neural network for enhanced direction finding with commodity 5G gNodeB
Shengheng Liu, Zihuan Mao, Xingkang Li +4
Pervasive and high-accuracy positioning has become increasingly important as a fundamental enabler for intelligent connected devices in mobile networks. Nevertheless, current wirel…
5G NR monostatic positioning with array impairments: Data-and-model-driven framework and experiment results
Shengheng Liu, Hao Wang, Mengguan Pan +3
In this article, we present an intelligent framework for 5G new radio (NR) indoor positioning under a monostatic configuration. The primary objective is to estimate both the angle…
Model-Driven Deep Neural Network for Enhanced AoA Estimation Using 5G gNB
Shengheng Liu, Xingkang Li, Zihuan Mao +2
High-accuracy positioning has become a fundamental enabler for intelligent connected devices. Nevertheless, the present wireless networks still rely on model-driven approaches to a…
Fine-grained graph representation learning for heterogeneous mobile networks with attentive fusion and contrastive learning
Shengheng Liu, Tianqi Zhang, Ningning Fu +1
AI becomes increasingly vital for telecom industry, as the burgeoning complexity of upcoming mobile communication networks places immense pressure on network operators. While there…