Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Jakob Hoydis"'
Autor:
Marco Di Renzo, Merouane Debbah, Dinh-Thuy Phan-Huy, Alessio Zappone, Mohamed-Slim Alouini, Chau Yuen, Vincenzo Sciancalepore, George C. Alexandropoulos, Jakob Hoydis, Haris Gacanin, Julien de Rosny, Ahcene Bounceur, Geoffroy Lerosey, Mathias Fink
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2019, Iss 1, Pp 1-20 (2019)
Abstract Future wireless networks are expected to constitute a distributed intelligent wireless communications, sensing, and computing platform, which will have the challenging requirement of interconnecting the physical and digital worlds in a seaml
Externí odkaz:
https://doaj.org/article/dbc95917d2ad4c38a660d3c2c57418ef
Autor:
Faycal Ait Aoudia, Jakob Hoydis
Publikováno v:
IEEE Transactions on Communications. 70:3804-3817
We propose a learning-based method for the joint design of a transmit and receive filter, the constellation geometry and associated bit labeling, as well as a neural network (NN)-based detector. The method maximizes an achievable information rate, wh
Autor:
Geoffrey Y. Li, Walid Saad, Ayfer Ozgur, Peter Kairouz, Zhijin Qin, Jakob Hoydis, Zhu Han, Deniz Gunduz, Jaafar Elmirghani
Publikováno v:
IEEE Journal on Selected Areas in Communications. 40:2251-2253
Autor:
Alvaro Valcarce, Jakob Hoydis
Publikováno v:
IEEE Transactions on Cognitive Communications and Networking. 7:1233-1243
Communication protocols are the languages used by network nodes. Before a user equipment (UE) can exchange data with a base station (BS), it must first negotiate the conditions and parameters for that transmission. This negotiation is supported by si
Autor:
Jakob Hoydis, Faris B. Mismar
Publikováno v:
IEEE Communications Letters. 25:3330-3334
This letter demonstrates the use of unsupervised machine learning to enable performance self-diagnosis of next-generation cellular networks. We propose two simplified applications of unsupervised learning that can enable real-time performance self-di
Autor:
Geoffrey Y. Li, Walid Saad, Ayfer Ozgur, Peter Kairouz, Zhijin Qin, Jakob Hoydis, Zhu Han, Deniz Gunduz, Jaafar Elmirghani
Publikováno v:
IEEE Journal on Selected Areas in Communications. 39:2267-2270
The Second Call for Papers of the Series on Machine Learning in Communications and Networks has continued to receive a great number of high-quality papers covering various aspects of intelligent communication systems. In addition to those already pub
Publikováno v:
2022 30th European Signal Processing Conference (EUSIPCO).
Publikováno v:
IEEE Communications Magazine. 59:76-81
Each generation of cellular communication systems is marked by a defining disruptive technology of its time, such as orthogonal frequency division multiplexing (OFDM) for 4G or Massive multiple-input multiple-output (MIMO) for 5G. Since artificial in
Autor:
Jakob Hoydis, H. Birkan Yilmaz, Chan-Byoung Chae, Timothy J. O'Shea, Namyoon Lee, Yansha Deng, Linglong Dai
Publikováno v:
Journal of Communications and Networks. 22:173-176
With recent advances, Artificial Intelligence (AI) and Machine Learning (ML) approaches have emerged to show great promise in the field of wireless communications. Although some researchers are skeptical due to issues concerning complexity and reliab