Zobrazeno 1 - 10
of 3 081
pro vyhledávání: '"SHEN, Xuemin"'
Autor:
Xu, Wenchao, Chen, Jinyu, Zheng, Peirong, Yi, Xiaoquan, Tian, Tianyi, Zhu, Wenhui, Wan, Quan, Wang, Haozhao, Fan, Yunfeng, Su, Qinliang, Shen, Xuemin
Foundation model (FM) powered agent services are regarded as a promising solution to develop intelligent and personalized applications for advancing toward Artificial General Intelligence (AGI). To achieve high reliability and scalability in deployin
Externí odkaz:
http://arxiv.org/abs/2412.13437
In this article, we propose a digital agent (DA)-assisted network management framework for future sixth generation (6G) networks considering users' quality of experience (QoE). Particularly, a novel QoE metric is defined by incorporating the impact o
Externí odkaz:
http://arxiv.org/abs/2412.14177
In this article, we present a novel user-centric service provision for immersive communications (IC) in 6G to deal with the uncertainty of individual user behaviors while satisfying unique requirements on the quality of multi-sensory experience. To t
Externí odkaz:
http://arxiv.org/abs/2410.02688
Autor:
He, Jiayi, Luo, Xiaofeng, Kang, Jiawen, Du, Hongyang, Xiong, Zehui, Chen, Ci, Niyato, Dusit, Shen, Xuemin
Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable solution for future efficient communication. Deep Learning (DL)-based semantic codecs further enhance this efficiency. However, the vulnerability of DL models to s
Externí odkaz:
http://arxiv.org/abs/2409.15695
Future 6G networks are envisioned to support mobile augmented reality (MAR) applications and provide customized immersive experiences for users via advanced service provision. In this paper, we investigate user-centric service provision for edge-assi
Externí odkaz:
http://arxiv.org/abs/2409.00324
Autor:
Wang, Jiacheng, Du, Hongyang, Liu, Yinqiu, Sun, Geng, Niyato, Dusit, Mao, Shiwen, Kim, Dong In, Shen, Xuemin
Integrated sensing and communications (ISAC) is expected to be a key technology for 6G, and channel state information (CSI) based sensing is a key component of ISAC. However, current research on ISAC focuses mainly on improving sensing performance, o
Externí odkaz:
http://arxiv.org/abs/2408.11398
Radio map (RM) is a promising technology that can obtain pathloss based on only location, which is significant for 6G network applications to reduce the communication costs for pathloss estimation. However, the construction of RM in traditional is ei
Externí odkaz:
http://arxiv.org/abs/2408.08593
Autor:
Liu, Yinqiu, Liu, Guangyuan, Du, Hongyang, Niyato, Dusit, Kang, Jiawen, Xiong, Zehui, Kim, Dong In, Shen, Xuemin
In the rapidly evolving Next-Generation Networking (NGN) era, the adoption of zero-trust architectures has become increasingly crucial to protect security. However, provisioning zero-trust services in NGNs poses significant challenges, primarily due
Externí odkaz:
http://arxiv.org/abs/2406.13964
This article presents a digital twin (DT)-enhanced reinforcement learning (RL) framework aimed at optimizing performance and reliability in network resource management, since the traditional RL methods face several unified challenges when applied to
Externí odkaz:
http://arxiv.org/abs/2406.07857
Publikováno v:
IEEE Internet Things J. (Volume: 11, Issue: 7, 01 April 2024)
Device-edge collaboration on deep neural network (DNN) inference is a promising approach to efficiently utilizing network resources for supporting artificial intelligence of things (AIoT) applications. In this paper, we propose a novel digital twin (
Externí odkaz:
http://arxiv.org/abs/2405.17664