Zobrazeno 1 - 10
of 137
pro vyhledávání: '"Ni, WanLi"'
With the rapid development of artificial intelligence, robotics, and Internet of Things, multi-robot systems are progressively acquiring human-like environmental perception and understanding capabilities, empowering them to complete complex tasks thr
Externí odkaz:
http://arxiv.org/abs/2412.09117
The robust beamforming design in multi-functional reconfigurable intelligent surface (MF-RIS) assisted wireless networks is investigated in this work, where the MF-RIS supports signal reflection, refraction, and amplification to address the double-fa
Externí odkaz:
http://arxiv.org/abs/2412.08032
As a paradigm of distributed machine learning, federated learning typically requires all edge devices to train a complete model locally. However, with the increasing scale of artificial intelligence models, the limited resources on edge devices often
Externí odkaz:
http://arxiv.org/abs/2412.06414
Autor:
Han, Dongsheng, Wang, Peng, Ni, Wanli, Wang, Wen, Zheng, Ailing, Niyato, Dusit, Al-Dhahir, Naofal
In this paper, we propose a novel multi-functional reconfigurable intelligent surface (MF-RIS) that supports signal reflection, refraction, amplification, and target sensing simultaneously. Our MF-RIS aims to enhance integrated communication and sens
Externí odkaz:
http://arxiv.org/abs/2412.01251
Autor:
Ni, Wanli, Wang, Wen, Zheng, Ailing, Wang, Peng, You, Changsheng, Eldar, Yonina C., Niyato, Dusit, Schober, Robert
In this article, we propose new network architectures that integrate multi-functional reconfigurable intelligent surfaces (MF-RISs) into 6G networks to enhance both communication and sensing capabilities. Firstly, we elaborate how to leverage MF-RISs
Externí odkaz:
http://arxiv.org/abs/2410.06584
In this letter, we design a federated contrastive learning (FedCL) framework aimed at supporting personalized semantic communication. Our FedCL enables collaborative training of local semantic encoders across multiple clients and a global semantic de
Externí odkaz:
http://arxiv.org/abs/2406.09182
Although reconfigurable intelligent surfaces (RISs) have demonstrated the potential to boost network capacity and expand coverage by adjusting their electromagnetic properties, existing RIS architectures have certain limitations, such as double-fadin
Externí odkaz:
http://arxiv.org/abs/2405.16257
Autor:
Ni, Wanli, Yang, Zhaohui
One key vision of intelligent Internet of Things (IoT) is to provide connected intelligence for a large number of application scenarios, such as self-driving cars, industrial manufacturing, and smart city. However, existing centralized or federated l
Externí odkaz:
http://arxiv.org/abs/2405.17453
Multi-Objective Optimization-Based Waveform Design for Multi-User and Multi-Target MIMO-ISAC Systems
Integrated sensing and communication (ISAC) opens up new service possibilities for sixth-generation (6G) systems, where both communication and sensing (C&S) functionalities co-exist by sharing the same hardware platform and radio resource. In this pa
Externí odkaz:
http://arxiv.org/abs/2405.13549
Although reconfigurable intelligent surface (RIS) can improve the secrecy communication performance of wireless users, it still faces challenges such as limited coverage and double-fading effect. To address these issues, in this paper, we utilize a n
Externí odkaz:
http://arxiv.org/abs/2405.10514