56 citations · 219 across the 24 of their papers we have counts for
24 papers
Dynamical Multimodal Fusion with Mixture-of-Experts for Localizations
Bohao Wang, Zitao Shuai, Fenghao Zhu +6
Multimodal fingerprinting is a crucial technique to sub-meter 6G integrated sensing and communications (ISAC) localization, but two hurdles block deployment: (i) the contribution e…
Implicit Neural Compression of Point Clouds
Hongning Ruan, Yulin Shao, Qianqian Yang +3
Point clouds have gained prominence across numerous applications due to their ability to accurately represent 3D objects and scenes. However, efficiently compressing unstructured,…
Green Probabilistic Semantic Communication over Wireless Networks
Ruopeng Xu, Zhaohui Yang, Yijie Mao +5
In this paper, we propose a multi-user green semantic communication system facilitated by a probabilistic knowledge graph (PKG). By integrating probability into the knowledge graph…
Robust Continuous-Time Beam Tracking with Liquid Neural Network
Fenghao Zhu, Xinquan Wang, Chongwen Huang +6
Millimeter-wave (mmWave) technology is increasingly recognized as a pivotal technology of the sixth-generation communication networks due to the large amounts of available spectrum…
A Joint Communication and Computation Design for Distributed RISs Assisted Probabilistic Semantic Communication in IIoT
Zhouxiang Zhao, Zhaohui Yang, Chongwen Huang +5
In this paper, the problem of spectral-efficient communication and computation resource allocation for distributed reconfigurable intelligent surfaces (RISs) assisted probabilistic…
Resource Allocation for Green Probabilistic Semantic Communication with Rate Splitting
Ruopeng Xu, Zhaohui Yang, Zhouxiang Zhao +2
In this paper, the energy efficient design for probabilistic semantic communication (PSC) system with rate splitting multiple access (RSMA) is investigated. Basic principles are fi…
Evolving Semantic Communication with Generative Model
Shunpu Tang, Qianqian Yang, Deniz Gündüz +1
Recently, learning-based semantic communication (SemCom) has emerged as a promising approach in the upcoming 6G network and researchers have made remarkable efforts in this field.…
A Superposition Code-Based Semantic Communication Approach with Quantifiable and Controllable Security
Weixuan Chen, Shuo Shao, Qianqian Yang +2
This paper addresses the challenge of achieving security in semantic communication (SemCom) over a wiretap channel, where a legitimate receiver coexists with an eavesdropper experi…
Multi-Sources Information Fusion Learning for Multi-Points NLOS Localization
Bohao Wang, Fenghao Zhu, Mengbing Liu +5
Accurate localization of mobile terminals is crucial for integrated sensing and communication systems. Existing fingerprint localization methods, which deduce coordinates from chan…
Point Cloud in the Air
Yulin Shao, Chenghong Bian, Li Yang +3
Acquisition and processing of point clouds (PCs) is a crucial enabler for many emerging applications reliant on 3D spatial data, such as robot navigation, autonomous vehicles, and…
Semantic Communication with Probability Graph: A Joint Communication and Computation Design
Zhouxiang Zhao, Zhaohui Yang, Quoc-Viet Pham +2
In this paper, we present a probability graph-based semantic information compression system for scenarios where the base station (BS) and the user share common background knowledge…
The Model Inversion Eavesdropping Attack in Semantic Communication Systems
Yuhao Chen, Qianqian Yang, Zhiguo Shi +1
In recent years, semantic communication has been a popular research topic for its superiority in communication efficiency. As semantic communication relies on deep learning to extr…
Semantic-aware Transmission for Robust Point Cloud Classification
Tianxiao Han, Kaiyi Chi, Qianqian Yang +1
As three-dimensional (3D) data acquisition devices become increasingly prevalent, the demand for 3D point cloud transmission is growing. In this study, we introduce a semantic-awar…
MIMO Precoding Design with QoS and Per-Antenna Power Constraints
Kaiyi Chi, Yingzhi Huang, Qianqian Yang +2
Precoding design for the downlink of multiuser multiple-input multiple-output (MU-MIMO) systems is a fundamental problem. In this paper, we aim to maximize the weighted sum rate (W…
Information-Theoretic Limits on Compression of Semantic Information
Jiancheng Tang, Qianqian Yang, Zhaoyang Zhang
As conventional communication systems based on classic information theory have closely approached the limits of Shannon channel capacity, semantic communication has been recognized…
Deep Joint Source-Channel Coding for Wireless Image Transmission with Entropy-Aware Adaptive Rate Control
Weixuan Chen, Yuhao Chen, Qianqian Yang +3
Adaptive rate control for deep joint source and channel coding (JSCC) is considered as an effective approach to transmit sufficient information in scenarios with limited communicat…
Semantic-aware Digital Twin for Metaverse: A Comprehensive Review
Senthil Kumar Jagatheesaperumal, Zhaohui Yang, Qianqian Yang +4
To facilitate the deployment of digital twins in Metaverse, the paradigm with semantic awareness has been proposed as a means for enabling accurate and task-oriented information ex…
Contrastive Learning based Semantic Communication for Wireless Image Transmission
Shunpu Tang, Qianqian Yang, Lisheng Fan +3
Recently, semantic communication has been widely applied in wireless image transmission systems as it can prioritize the preservation of meaningful semantic information in images o…
Cooperative Task-Oriented Communication for Multi-Modal Data with Transmission Control
Shiqi Wang, Qianqian Yang, Zhiguo Shi +2
Real-time intelligence applications in Internet of Things (IoT) environment depend on timely data communication. However, it is challenging to transmit and analyse massive data of…
Resource Allocation for Capacity Optimization in Joint Source-Channel Coding Systems
Kaiyi Chi, Qianqian Yang, Zhaohui Yang +2
Benefited from the advances of deep learning (DL) techniques, deep joint source-channel coding (JSCC) has shown its great potential to improve the performance of wireless transmiss…
Generative Model Based Highly Efficient Semantic Communication Approach for Image Transmission
Tianxiao Han, Jiancheng Tang, Qianqian Yang +3
Deep learning (DL) based semantic communication methods have been explored to transmit images efficiently in recent years. In this paper, we propose a generative model based semant…
Semantic-preserved Communication System for Highly Efficient Speech Transmission
Tianxiao Han, Qianqian Yang, Zhiguo Shi +2
Deep learning (DL) based semantic communication methods have been explored for the efficient transmission of images, text, and speech in recent years. In contrast to traditional wi…
Blind Channel Estimation for MIMO Systems via Variational Inference
Jiancheng Tang, Qianqian Yang, Zhaoyang Zhang
In this paper, we investigate the blind channel estimation problem for MIMO systems under Rayleigh fading channel. Conventional MIMO communication techniques require transmitting a…
Communication-Efficient Federated Learning with Binary Neural Networks
Yuzhi Yang, Zhaoyang Zhang, Qianqian Yang
Federated learning (FL) is a privacy-preserving machine learning setting that enables many devices to jointly train a shared global model without the need to reveal their data to a…