Zobrazeno 1 - 10
of 351
pro vyhledávání: '"Arora, Anish"'
Achieving low duty cycle operation in low-power wireless networks in urban environments is complicated by the complex and variable dynamics of external interference and fading. We explore the use of reinforcement learning for achieving low power cons
Externí odkaz:
http://arxiv.org/abs/2410.05147
Autor:
Nadim, Md, Islam, Taimoor Ul, Reddy, Salil, Zhang, Tianyi, Meng, Zhibo, Afzal, Reshal, Babu, Sarath, Ahmad, Arsalan, Qiao, Daji, Arora, Anish, Zhang, Hongwei
Time synchronization is a critical component in network operation and management, and it is also required by Ultra-Reliable, Low-Latency Communications (URLLC) in next-generation wireless systems such as those of 5G, 6G, and Open RAN. In this context
Externí odkaz:
http://arxiv.org/abs/2410.03583
Autor:
Islam, Taimoor Ul, Boateng, Joshua Ofori, Nadim, Md, Zu, Guoying, Shahid, Mukaram, Li, Xun, Zhang, Tianyi, Reddy, Salil, Xu, Wei, Atalar, Ataberk, Lee, Vincent, Chen, Yung-Fu, Gosling, Evan, Permatasari, Elisabeth, Somiah, Christ, Meng, Zhibo, Babu, Sarath, Soliman, Mohammed, Hussain, Ali, Qiao, Daji, Zheng, Mai, Boyraz, Ozdal, Guan, Yong, Arora, Anish, Selim, Mohamed, Ahmad, Arsalan, Cohen, Myra B., Luby, Mike, Chandra, Ranveer, Gross, James, Zhang, Hongwei
To address the rural broadband challenge and to leverage the unique opportunities that rural regions provide for piloting advanced wireless applications, we design and implement the ARA wireless living lab for research and innovation in rural wireles
Externí odkaz:
http://arxiv.org/abs/2408.00913
We propose a learning algorithm for local routing policies that needs only a few data samples obtained from a single graph while generalizing to all random graphs in a standard model of wireless networks. We thus solve the all-pairs near-shortest pat
Externí odkaz:
http://arxiv.org/abs/2308.09829
Routing in wireless meshes must detour around holes. Extant routing protocols often underperform in minimally connected networks where holes are larger and more frequent. Minimal density networks are common in practice due to deployment cost constrai
Externí odkaz:
http://arxiv.org/abs/2305.05718
Autor:
Chen, Yung-Fu, Arora, Anish
The throughput efficiency of a wireless mesh network with potentially malicious external or internal interference can be significantly improved by equipping routers with multi-radio access over multiple channels. For reliably mitigating the effect of
Externí odkaz:
http://arxiv.org/abs/2212.08161
Autor:
Srivastava, Sangeeta, Wu, Ho-Hsiang, Rulff, Joao, Fuentes, Magdalena, Cartwright, Mark, Silva, Claudio, Arora, Anish, Bello, Juan Pablo
Audio applications involving environmental sound analysis increasingly use general-purpose audio representations, also known as embeddings, for transfer learning. Recently, Holistic Evaluation of Audio Representations (HEAR) evaluated twenty-nine emb
Externí odkaz:
http://arxiv.org/abs/2203.10425
Autor:
Yun, Jihoon, Srivastava, Sangeeta, Roy, Dhrubojyoti, Stohs, Nathan, Mydlarz, Charlie, Salman, Mahin, Steers, Bea, Bello, Juan Pablo, Arora, Anish
The Sounds of New York City (SONYC) wireless sensor network (WSN) has been fielded in Manhattan and Brooklyn over the past five years, as part of a larger human-in-the-loop cyber-physical control system for monitoring, analyzing, and mitigating urban
Externí odkaz:
http://arxiv.org/abs/2203.06220
Autor:
Srivastava, Sangeeta, Olin, Samuel, Podolskiy, Viktor, Karpatne, Anuj, Lee, Wei-Cheng, Arora, Anish
Given their ability to effectively learn non-linear mappings and perform fast inference, deep neural networks (NNs) have been proposed as a viable alternative to traditional simulation-driven approaches for solving high-dimensional eigenvalue equatio
Externí odkaz:
http://arxiv.org/abs/2202.05994