Zobrazeno 1 - 10
of 4 323
pro vyhledávání: '"Shah P. K."'
The advancement of 5G and NextG networks through Open Radio Access Network (O-RAN) architecture enables a shift toward virtualized, modular, and disaggregated configurations. A core component of O-RAN is the RAN Intelligent Controller (RIC), which ma
Externí odkaz:
http://arxiv.org/abs/2411.07128
Drought has been perceived as a persistent threat globally and the complex mechanism of various factors contributing to its emergence makes it more troublesome to understand. Droughts and their severity trends have been a point of concern in the USA
Externí odkaz:
http://arxiv.org/abs/2411.04303
Autor:
Dhungel, Sarik, Duggal, Gaurav, Ron, Dara, Tripathi, Nishith, Buehrer, R. Michael, Reed, Jeffrey H., Shah, Vijay K
The advent of 5G positioning techniques by 3GPP has unlocked possibilities for applications in public safety, vehicular systems, and location-based services. However, these applications demand accurate and reliable positioning performance, which has
Externí odkaz:
http://arxiv.org/abs/2410.18323
Autor:
Gajjar, Pranshav, Shah, Vijay K.
Large Language Models (LLMs) can revolutionize how we deploy and operate Open Radio Access Networks (O-RAN) by enhancing network analytics, anomaly detection, and code generation and significantly increasing the efficiency and reliability of a pletho
Externí odkaz:
http://arxiv.org/abs/2407.06245
Autor:
Prabhakar, Raghu, Sivaramakrishnan, Ram, Gandhi, Darshan, Du, Yun, Wang, Mingran, Song, Xiangyu, Zhang, Kejie, Gao, Tianren, Wang, Angela, Li, Karen, Sheng, Yongning, Brot, Joshua, Sokolov, Denis, Vivek, Apurv, Leung, Calvin, Sabnis, Arjun, Bai, Jiayu, Zhao, Tuowen, Gottscho, Mark, Jackson, David, Luttrell, Mark, Shah, Manish K., Chen, Edison, Liang, Kaizhao, Jain, Swayambhoo, Thakker, Urmish, Huang, Dawei, Jairath, Sumti, Brown, Kevin J., Olukotun, Kunle
Monolithic large language models (LLMs) like GPT-4 have paved the way for modern generative AI applications. Training, serving, and maintaining monolithic LLMs at scale, however, remains prohibitively expensive and challenging. The disproportionate i
Externí odkaz:
http://arxiv.org/abs/2405.07518
Autor:
Nguyen, Vuong D., Shah, Shishir K.
Long-term Person Re-Identification (LRe-ID) aims at matching an individual across cameras after a long period of time, presenting variations in clothing, pose, and viewpoint. In this work, we propose CCPA: Contrastive Clothing and Pose Augmentation f
Externí odkaz:
http://arxiv.org/abs/2402.14454
Deep learning offers a promising solution to improve spectrum access techniques by utilizing data-driven approaches to manage and share limited spectrum resources for emerging applications. For several of these applications, the sensitive wireless da
Externí odkaz:
http://arxiv.org/abs/2402.09710
In the midst of the rapid integration of artificial intelligence (AI) into real world applications, one pressing challenge we confront is the phenomenon of model drift, wherein the performance of AI models gradually degrades over time, compromising t
Externí odkaz:
http://arxiv.org/abs/2402.07258
While the open architecture, open interfaces, and integration of intelligence within Open Radio Access Network technology hold the promise of transforming 5G and 6G networks, they also introduce cybersecurity vulnerabilities that hinder its widesprea
Externí odkaz:
http://arxiv.org/abs/2402.06846
Autor:
Niloy, Ta-seen Reaz, Kumar, Saurav, Hore, Aniruddha, Hassan, Zoheb, Dietrich, Carl, Burger, Eric W., Reed, Jeffrey H., Shah, Vijay K.
This paper introduces ASCENT (context Aware Spectrum Coexistence Design and Implementation) toolset, an advanced context-aware terrestrial satellite spectrum sharing toolset designed for researchers, policymakers, and regulators. It serves two essent
Externí odkaz:
http://arxiv.org/abs/2402.05273