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pro vyhledávání: '"Vijay, 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
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:
Streit, Robert, Garg, Vijay K.
Matroids provide one of the most elegant structures for algorithm design. This is best identified by the Edmonds-Rado theorem relating the success of the simple greedy algorithm to the anatomy of the optimal basis of a matroid [Edm71; Rad57]. As a re
Externí odkaz:
http://arxiv.org/abs/2408.04118
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:
Phatak, Atharva, Mago, Vijay K., Agrawal, Ameeta, Inbasekaran, Aravind, Giabbanelli, Philippe J.
Publikováno v:
Proceedings of the 57th Hawaii International Conference on System Sciences 2024
The use of generative AI to create text descriptions from graphs has mostly focused on knowledge graphs, which connect concepts using facts. In this work we explore the capability of large pretrained language models to generate text from causal graph
Externí odkaz:
http://arxiv.org/abs/2403.07118
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
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
Spectrum sharing between terrestrial 5G and incumbent networks in the satellite bands presents a promising avenue to satisfy the ever-increasing bandwidth demand of the next-generation wireless networks. However, protecting incumbent operations from
Externí odkaz:
http://arxiv.org/abs/2402.04447
Automatic Speech Recognition (ASR) systems are used in the financial domain to enhance the caller experience by enabling natural language understanding and facilitating efficient and intuitive interactions. Increasing use of ASR systems requires that
Externí odkaz:
http://arxiv.org/abs/2402.01931