Zobrazeno 1 - 10
of 932
pro vyhledávání: '"Wang, Jiangzhou"'
Autor:
Zhang, Cui, Zhang, Wenjun, Wu, Qiong, Fan, Pingyi, Fan, Qiang, Wang, Jiangzhou, Letaief, Khaled B.
Federated Learning (FL) can protect the privacy of the vehicles in vehicle edge computing (VEC) to a certain extent through sharing the gradients of vehicles' local models instead of local data. The gradients of vehicles' local models are usually lar
Externí odkaz:
http://arxiv.org/abs/2407.08462
As a promising technology, vehicular edge computing (VEC) can provide computing and caching services by deploying VEC servers near vehicles. However, VEC networks still face challenges such as high vehicle mobility. Digital twin (DT), an emerging tec
Externí odkaz:
http://arxiv.org/abs/2407.07575
Autor:
Ji, Maoxin, Wu, Qiong, Fan, Pingyi, Cheng, Nan, Chen, Wen, Wang, Jiangzhou, Letaief, Khaled B.
In the rapidly evolving landscape of Internet of Vehicles (IoV) technology, Cellular Vehicle-to-Everything (C-V2X) communication has attracted much attention due to its superior performance in coverage, latency, and throughput. Resource allocation wi
Externí odkaz:
http://arxiv.org/abs/2407.06518
Autor:
Wang, Wenhua, Wu, Qiong, Fan, Pingyi, Cheng, Nan, Chen, Wen, Wang, Jiangzhou, Letaief, Khaled B.
With the rapid development of intelligent vehicles and Intelligent Transport Systems (ITS), the sensors such as cameras and LiDAR installed on intelligent vehicles provides higher capacity of executing computation-intensive and delay-sensitive tasks,
Externí odkaz:
http://arxiv.org/abs/2407.02342
Autor:
Li, Yupeng, Li, Gang, Wen, Zirui, Han, Shuangfeng, Gao, Shijian, Liu, Guangyi, Wang, Jiangzhou
The AI-enabled autoencoder has demonstrated great potential in channel state information (CSI) feedback in frequency division duplex (FDD) multiple input multiple output (MIMO) systems. However, this method completely changes the existing feedback st
Externí odkaz:
http://arxiv.org/abs/2407.00896
Vehicular edge computing (VEC) is an emerging technology that enables vehicles to perform high-intensity tasks by executing tasks locally or offloading them to nearby edge devices. However, obstacles such as buildings may degrade the communications a
Externí odkaz:
http://arxiv.org/abs/2406.11318
Autor:
Qi, Kangwei, Wu, Qiong, Fan, Pingyi, Cheng, Nan, Chen, Wen, Wang, Jiangzhou, Letaief, Khaled B.
Reconfigurable Intelligent Surface (RIS) is a pivotal technology in communication, offering an alternative path that significantly enhances the link quality in wireless communication environments. In this paper, we propose a RIS-assisted internet of
Externí odkaz:
http://arxiv.org/abs/2406.11245
Autor:
Li, Yifan, Shu, Feng, Bai, Jiatong, Pan, Cunhua, Wu, Yongpeng, Song, Yaoliang, Wang, Jiangzhou
A fully-digital massive MIMO receive array is promising to meet the high-resolution requirement of near-field (NF) emitter localization, but it also results in the significantly increasing of hardware costs and algorithm complexity. In order to meet
Externí odkaz:
http://arxiv.org/abs/2406.09695
This letter proposes a semantic-aware resource allocation (SARA) framework with flexible duty cycle (DC) coexistence mechanism (SARADC) for 5G-V2X Heterogeneous Network (HetNets) based on deep reinforcement learning (DRL) proximal policy optimization
Externí odkaz:
http://arxiv.org/abs/2406.07996
Autor:
Shao, Zhiyu, Wu, Qiong, Fan, Pingyi, Cheng, Nan, Chen, Wen, Wang, Jiangzhou, Letaief, Khaled B.
This work aims to investigate semantic communication in high-speed mobile Internet of vehicles (IoV) environments, with a focus on the spectrum sharing between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. We specifical
Externí odkaz:
http://arxiv.org/abs/2406.07213