Zobrazeno 1 - 10
of 305
pro vyhledávání: '"Pham, Quoc Viet"'
Autor:
Van Huynh, Nguyen, Zhang, Bolun, Tran, Dinh-Hieu, Hoang, Dinh Thai, Nguyen, Diep N., Zheng, Gan, Niyato, Dusit, Pham, Quoc-Viet
Spectrum access is an essential problem in device-to-device (D2D) communications. However, with the recent growth in the number of mobile devices, the wireless spectrum is becoming scarce, resulting in low spectral efficiency for D2D communications.
Externí odkaz:
http://arxiv.org/abs/2410.17971
Autor:
Aouedi, Ons, Vu, Thai-Hoc, Sacco, Alessio, Nguyen, Dinh C., Piamrat, Kandaraj, Marchetto, Guido, Pham, Quoc-Viet
The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techniques have been exploited to facilitate IoT operations and maximize the
Externí odkaz:
http://arxiv.org/abs/2406.03820
Autor:
Vu, Thai-Hoc, Jagatheesaperumal, Senthil Kumar, Nguyen, Minh-Duong, Van Huynh, Nguyen, Kim, Sunghwan, Pham, Quoc-Viet
The success of Artificial Intelligence (AI) in multiple disciplines and vertical domains in recent years has promoted the evolution of mobile networking and the future Internet toward an AI-integrated Internet-of-Things (IoT) era. Nevertheless, most
Externí odkaz:
http://arxiv.org/abs/2405.20024
The End-to-end (E2E) learning-based approach has great potential to reshape the existing communication systems by replacing the transceivers with deep neural networks. To this end, the E2E learning approach needs to assume the availability of prior c
Externí odkaz:
http://arxiv.org/abs/2404.06257
Autor:
Zhao, Zhouxiang, Yang, Zhaohui, Gan, Xu, Pham, Quoc-Viet, Huang, Chongwen, Xu, Wei, Zhang, Zhaoyang
In this paper, we delve into the challenge of optimizing joint communication and computation for semantic communication over wireless networks using a probability graph framework. In the considered model, the base station (BS) extracts the small-size
Externí odkaz:
http://arxiv.org/abs/2312.13975
In this paper, we investigate time-division based framework for integrated sensing, communication, and computing in integrated satellite-terrestrial networks. We consider a scenario, where Internet-of-Things devices on the ground operate with sensing
Externí odkaz:
http://arxiv.org/abs/2311.02415
The emergence of new services and applications in emerging wireless networks (e.g., beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) in the Internet of Things (IoT). However, the proliferation of massive IoT
Externí odkaz:
http://arxiv.org/abs/2310.10549
Autor:
Luu, Minh Ngoc, Nguyen, Minh-Duong, Bedeer, Ebrahim, Nguyen, Van Duc, Hoang, Dinh Thai, Nguyen, Diep N., Pham, Quoc-Viet
In the domain of Federated Learning (FL) systems, recent cutting-edge methods heavily rely on ideal conditions convergence analysis. Specifically, these approaches assume that the training datasets on IoT devices possess similar attributes to the glo
Externí odkaz:
http://arxiv.org/abs/2310.07497
Recent research efforts on semantic communication have mostly considered accuracy as a main problem for optimizing goal-oriented communication systems. However, these approaches introduce a paradox: the accuracy of artificial intelligence (AI) tasks
Externí odkaz:
http://arxiv.org/abs/2309.14587
This paper explores Large Batch Training techniques using layer-wise adaptive scaling ratio (LARS) across diverse settings, uncovering insights. LARS algorithms with warm-up tend to be trapped in sharp minimizers early on due to redundant ratio scali
Externí odkaz:
http://arxiv.org/abs/2309.14053