Zobrazeno 1 - 10
of 1 484
pro vyhledávání: '"Debbah, Merouane"'
This paper addresses the mobility problem with the assistance of fluid antenna (FA) on the user equipment (UE) side. We propose a matrix pencil-based moving port (MPMP) prediction method, which may transform the time-varying channel to a static chann
Externí odkaz:
http://arxiv.org/abs/2408.04320
Autor:
Mohamad, Hassan, Zhang, Chao, Lasaulce, Samson, Varma, Vineeth S, Debbah, Mérouane, Ghogho, Mounir
Federated learning (FL) involves several clients that share with a fusion center (FC), the model each client has trained with its own data. Conventional FL, which can be interpreted as an estimation or distortion-based approach, ignores the final use
Externí odkaz:
http://arxiv.org/abs/2408.02384
Semantic communication leveraging advanced deep learning (DL) technologies enhances the efficiency, reliability, and security of information transmission. Emerging stacked intelligent metasurface (SIM) having a diffractive neural network (DNN) archit
Externí odkaz:
http://arxiv.org/abs/2407.15053
In this paper, we consider controlled linear dynamical systems in which the controller has only access to a compressed version of the system state. The technical problem we investigate is that of allocating compression resources over time such that t
Externí odkaz:
http://arxiv.org/abs/2407.10224
Autor:
Zou, Hang, Zhao, Qiyang, Tian, Yu, Bariah, Lina, Bader, Faouzi, Lestable, Thierry, Debbah, Merouane
Large Language Models (LLMs) have the potential to revolutionize the Sixth Generation (6G) communication networks. However, current mainstream LLMs generally lack the specialized knowledge in telecom domain. In this paper, for the first time, we prop
Externí odkaz:
http://arxiv.org/abs/2407.09424
Autor:
Wang, Li, Zhang, Chao, Zhao, Qiyang, Zou, Hang, Lasaulce, Samson, Valenzise, Giuseppe, He, Zhuo, Debbah, Merouane
The development of wireless sensing technologies, using signals such as Wi-Fi, infrared, and RF to gather environmental data, has significantly advanced within Internet of Things (IoT) systems. Among these, Radio Frequency (RF) sensing stands out for
Externí odkaz:
http://arxiv.org/abs/2407.07506
It has been well known that the achievable rate of multiuser multiple-input multiple-output systems with limited feedback is severely degraded by quantization errors when the number of feedback bits is not sufficient. To overcome such a rate degradat
Externí odkaz:
http://arxiv.org/abs/2407.05636
Autor:
Gan, Xu, Huang, Chongwen, Yang, Zhaohui, Chen, Xiaoming, Bader, Faouzi, Zhang, Zhaoyang, Yuen, Chau, Guan, Yong Liang, Debbah, Merouane
Integrated sensing and communication (ISAC) has emerged as a promising technology to facilitate high-rate communications and super-resolution sensing, particularly operating in the millimeter wave (mmWave) band. However, the vulnerability of mmWave s
Externí odkaz:
http://arxiv.org/abs/2407.05249
Autor:
Yang, Songjie, An, Jiancheng, Xiu, Yue, Lyu, Wanting, Ning, Boyu, Zhang, Zhongpei, Debbah, Merouane, Yuen, Chau
Flexible antenna arrays (FAAs), distinguished by their rotatable, bendable, and foldable properties, are extensively employed in flexible radio systems to achieve customized radiation patterns. This paper aims to illustrate that FAAs, capable of dyna
Externí odkaz:
http://arxiv.org/abs/2407.04944
This paper presents a cooperative multi-agent deep reinforcement learning (MADRL) approach for unmmaned aerial vehicle (UAV)-aided mobile edge computing (MEC) networks. An UAV with computing capability can provide task offlaoding services to ground i
Externí odkaz:
http://arxiv.org/abs/2407.03280