Search Results for author: Xianfu Chen

Found 20 papers, 3 papers with code

Select2Col: Leveraging Spatial-Temporal Importance of Semantic Information for Efficient Collaborative Perception

1 code implementation31 Jul 2023 Yuntao Liu, Qian Huang, Rongpeng Li, Xianfu Chen, Zhifeng Zhao, Shuyuan Zhao, Yongdong Zhu, Honggang Zhang

Collaborative perception by leveraging the shared semantic information plays a crucial role in overcoming the individual limitations of isolated agents.

Semantics-enhanced Temporal Graph Networks for Content Popularity Prediction

no code implementations29 Jan 2023 Jianhang Zhu, Rongpeng Li, Xianfu Chen, Shiwen Mao, Jianjun Wu, Zhifeng Zhao

On top of that, we customize its temporal and structural learning modules to further boost the prediction performance.

Graph Learning

Adversarial Learning for Implicit Semantic-Aware Communications

no code implementations27 Jan 2023 Zhimin Lu, Yong Xiao, Zijian Sun, Yingyu Li, Guangming Shi, Xianfu Chen, Mehdi Bennis, H. Vincent Poor

In this paper, we consider the implicit semantic communication problem in which hidden relations and closely related semantic terms that cannot be recognized from the source signals need to also be delivered to the destination user.

Semantics-Empowered Communication: A Tutorial-cum-Survey

no code implementations16 Dec 2022 Zhilin Lu, Rongpeng Li, Kun Lu, Xianfu Chen, Ekram Hossain, Zhifeng Zhao, Honggang Zhang

Along with the springing up of the semantics-empowered communication (SemCom) research, it is now witnessing an unprecedentedly growing interest towards a wide range of aspects (e. g., theories, applications, metrics and implementations) in both academia and industry.

Age of Semantics in Cooperative Communications: To Expedite Simulation Towards Real via Offline Reinforcement Learning

no code implementations19 Sep 2022 Xianfu Chen, Zhifeng Zhao, Shiwen Mao, Celimuge Wu, Honggang Zhang, Mehdi Bennis

We then put forward a novel offline DAC scheme, which estimates the optimal control policy from a previously collected dataset without any further interactions with the system.

Reinforcement Learning (RL)

Rethinking Modern Communication from Semantic Coding to Semantic Communication

no code implementations16 Oct 2021 Kun Lu, Qingyang Zhou, Rongpeng Li, Zhifeng Zhao, Xianfu Chen, Jianjun Wu, Honggang Zhang

Modern communications are usually designed to pursue a higher bit-level precision and fewer bits while transmitting a message.

Reinforcement Learning (RL)

Reinforcement Learning-powered Semantic Communication via Semantic Similarity

1 code implementation27 Aug 2021 Kun Lu, Rongpeng Li, Xianfu Chen, Zhifeng Zhao, Honggang Zhang

We introduce a new semantic communication mechanism - SemanticRL, whose key idea is to preserve the semantic information instead of strictly securing the bit-level precision.

reinforcement-learning Reinforcement Learning (RL) +2

Learning-based WiFi Traffic Load Estimation in NR-U Systems

no code implementations8 Feb 2021 Rui Yin, Zhiqun Zou, Celimuge Wu, Jiantao Yuan, Xianfu Chen, Guanding Yu

An unsupervised Neural Network (NN) structure is applied to filter the detected transmission collision probability on the unlicensed spectrum, which enables the NR users to precisely rectify the measurement error and estimate the number of active WiFi users.

Information Theory Information Theory

Distributed Spectrum and Power Allocation for D2D-U Networks: A Scheme based on NN and Federated Learning

no code implementations8 Feb 2021 Rui Yin, Zhiqun Zou, Celimuge Wu, Jiantao Yuan, Xianfu Chen

In this paper, a Device-to-Device communication on unlicensed bands (D2D-U) enabled network is studied.

Fairness Federated Learning Information Theory Information Theory

DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoV

1 code implementation3 Sep 2020 Pengyuan Zhou, Xianfu Chen, Zhi Liu, Tristan Braud, Pan Hui, Jussi Kangasharju

To this end, we propose a Decentralized Reinforcement Learning at the Edge for traffic light control in the IoV (DRLE).

Edge-computing Management +3

Computation Offloading in Beyond 5G Networks: A Distributed Learning Framework and Applications

no code implementations15 Jul 2020 Xianfu Chen, Celimuge Wu, Zhi Liu, Ning Zhang, Yusheng Ji

Facing the trend of merging wireless communications and multi-access edge computing (MEC), this article studies computation offloading in the beyond fifth-generation networks.

Edge-computing Reinforcement Learning (RL)

Age of Information-Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective

no code implementations6 Aug 2019 Xianfu Chen, Celimuge Wu, Tao Chen, Honggang Zhang, Zhi Liu, Yan Zhang, Mehdi Bennis

In this paper, we investigate the problem of age of information (AoI)-aware radio resource management for expected long-term performance optimization in a Manhattan grid vehicle-to-vehicle network.

Decision Making Management +1

GAN-powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

no code implementations10 May 2019 Yuxiu Hua, Rongpeng Li, Zhifeng Zhao, Xianfu Chen, Honggang Zhang

Moreover, we further develop Dueling GAN-DDQN, which uses a specially designed dueling generator, to learn the action-value distribution by estimating the state-value distribution and the action advantage function.

Distributional Reinforcement Learning Generative Adversarial Network +3

Deep Learning with Long Short-Term Memory for Time Series Prediction

no code implementations24 Oct 2018 Yuxiu Hua, Zhifeng Zhao, Rongpeng Li, Xianfu Chen, Zhiming Liu, Honggang Zhang

Time series prediction can be generalized as a process that extracts useful information from historical records and then determines future values.

Time Series Time Series Prediction

Deep Reinforcement Learning for Resource Management in Network Slicing

no code implementations17 May 2018 Rongpeng Li, Zhifeng Zhao, Qi Sun, Chi-Lin I, Chenyang Yang, Xianfu Chen, MinJian Zhao, Honggang Zhang

Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices.

Management reinforcement-learning +1

Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning

no code implementations16 May 2018 Xianfu Chen, Honggang Zhang, Celimuge Wu, Shiwen Mao, Yusheng Ji, Mehdi Bennis

To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is a promising paradigm by providing computing capabilities in close proximity within a sliced radio access network (RAN), which supports both traditional communication and MEC services.

Edge-computing reinforcement-learning +1

Traffic Prediction Based on Random Connectivity in Deep Learning with Long Short-Term Memory

no code implementations8 Nov 2017 Yuxiu Hua, Zhifeng Zhao, Rongpeng Li, Xianfu Chen, Zhiming Liu, Honggang Zhang

So, the RCLSTM, with certain intrinsic sparsity, have many neural connections absent (distinguished from the full connectivity) and which leads to the reduction of the parameters to be trained and the computational cost.

Traffic Prediction

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

no code implementations28 Nov 2012 Rongpeng Li, Zhifeng Zhao, Xianfu Chen, Jacques Palicot, Honggang Zhang

Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs).

reinforcement-learning Reinforcement Learning (RL)

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