1.6k citations · 3.2k across the 55 of their papers we have counts for
24 papers · 1 filter
Meta Federated Reinforcement Learning for Distributed Resource Allocation
Zelin Ji, Zhijin Qin, Xiaoming Tao
In cellular networks, resource allocation is usually performed in a centralized way, which brings huge computation complexity to the base station (BS) and high transmission overhea…
Semantic Communication with Memory
Huiqiang Xie, Zhijin Qin, Geoffrey Ye Li
While semantic communication succeeds in efficiently transmitting due to the strong capability to extract the essential semantic information, it is still far from the intelligent o…
Semantic Communications with Variable-Length Coding for Extended Reality
Bowen Zhang, Zhijin Qin, Geoffrey Ye Li
Wireless extended reality (XR) has attracted wide attentions as a promising technology to improve users' mobility and quality of experience. However, the ultra-high data rate requi…
Resource Optimization for Semantic-Aware Networks with Task Offloading
Zelin Ji, Zhijin Qin, Xiaoming Tao +1
The limited capabilities of user equipment restrict the local implementation of computation-intensive applications. Edge computing, especially the edge intelligence system, enables…
A Generalized Semantic Communication System: from Sources to Channels
Zhijin Qin, Feifei Gao, Bo Lin +3
Semantic communication is regarded as the breakthrough beyond the Shannon paradigm, which transmits only semantic information to significantly improve communication efficiency. Thi…
Semantic Sensing and Communications for Ultimate Extended Reality
Bowen Zhang, Zhijin Qin, Yiyu Guo +1
As a key technology in metaversa, wireless ultimate extended reality (XR) has attracted extensive attentions from both industry and academia. However, the stringent latency and ult…
A Unified Multi-Task Semantic Communication System for Multimodal Data
Guangyi Zhang, Qiyu Hu, Zhijin Qin +3
Task-oriented semantic communications have achieved significant performance gains. However, the employed deep neural networks in semantic communications have to be updated when the…
A Robust Deep Learning Enabled Semantic Communication System for Text
Xiang Peng, Zhijin Qin, Danlan Huang +4
With the advent of the 6G era, the concept of semantic communication has attracted increasing attention. Compared with conventional communication systems, semantic communication sy…
Robust Semantic Communications with Masked VQ-VAE Enabled Codebook
Qiyu Hu, Guangyi Zhang, Zhijin Qin +3
Although semantic communications have exhibited satisfactory performance for a large number of tasks, the impact of semantic noise and the robustness of the systems have not been w…
A Unified Multi-Task Semantic Communication System with Domain Adaptation
Guangyi Zhang, Qiyu Hu, Zhijin Qin +2
The task-oriented semantic communication systems have achieved significant performance gain, however, the paradigm that employs a model for a specific task might be limited, since…
QoE-Aware Resource Allocation for Semantic Communication Networks
Lei Yan, Zhijin Qin, Rui Zhang +2
With the aim of accomplishing intelligence tasks, semantic communications transmit task-related information only, yielding significant performance gains over conventional communica…
Federated Learning for Distributed Energy-Efficient Resource Allocation
Zelin Ji, Zhijin Qin
In cellular networks, resource allocation is performed in a centralized way, which brings huge computation complexity to the base station (BS) and high transmission overhead. This…
Robust Semantic Communications Against Semantic Noise
Qiyu Hu, Guangyi Zhang, Zhijin Qin +3
Although the semantic communications have exhibited satisfactory performance in a large number of tasks, the impact of semantic noise and the robustness of the systems have not bee…
Resource allocation for text semantic communications
Lei Yan, Zhijin Qin, Rui Zhang +2
Semantic communications have shown its great potential to improve the transmission reliability, especially in the low signal-to-noise regime. However, resource allocation for seman…
Task-Oriented Multi-User Semantic Communications
Huiqiang Xie, Zhijin Qin, Xiaoming Tao +1
While semantic communications have shown the potential in the case of single-modal single-users, its applications to the multi-user scenario remain limited. In this paper, we inves…
Task-Oriented Multi-User Semantic Communications for VQA Task
Huiqiang Xie, Zhijin Qin, Geoffrey Ye Li
Semantic communications focus on the transmission of semantic features. In this letter, we consider a task-oriented multi-user semantic communication system for multimodal data tra…
Semantic Communication Systems for Speech Transmission
Zhenzi Weng, Zhijin Qin
Semantic communications could improve the transmission efficiency significantly by exploring the semantic information. In this paper, we make an effort to recover the transmitted s…
Joint User Activity and Data Detection in Grant-Free NOMA using Generative Neural Networks
Yixuan Zou, Zhijin Qin, Yuanwei Liu
Grant-free non-orthogonal multiple access (NOMA) is considered as one of the supporting technology for massive connectivity for future networks. In the grant-free NOMA systems with…
A Lite Distributed Semantic Communication System for Internet of Things
Huiqiang Xie, Zhijin Qin
The rapid development of deep learning (DL) and widespread applications of Internet-of-Things (IoT) have made the devices smarter than before, and enabled them to perform more inte…
Reconfigurable Intelligent Surfaces: Principles and Opportunities
Yuanwei Liu, Xiao Liu, Xidong Mu +4
Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs), have received significant attention for thei…
Reconfigurable Intelligent Surface Enhanced Device-to-Device Communications
Zelin Ji, Zhijin Qin
Reconfigurable intelligent surface (RIS) technology is a promising method to enhance the device-to-device (D2D) communications. To maximize the sum rate of the cellular and D2D net…
Deep Learning Enabled Semantic Communication Systems
Huiqiang Xie, Zhijin Qin, Geoffrey Ye Li +1
Recently, deep learned enabled end-to-end (E2E) communication systems have been developed to merge all physical layer blocks in the traditional communication systems, which make jo…
Resource Allocation for Edge Computing in IoT Networks via Reinforcement Learning
Xiaolan Liu, Zhijin Qin, Yue Gao
In this paper, we consider resource allocation for edge computing in internet of things (IoT) networks. Specifically, each end device is considered as an agent, which makes its dec…
UAV Communications Based on Non-Orthogonal Multiple Access
Yuanwei Liu, Zhijin Qin, Yunlong Cai +3
This article proposes a novel framework for unmaned aerial vehicle (UAV) networks with massive access capability supported by non-orthogonal multiple access (NOMA). In order to bet…