all AI news
Deep Joint Source-Channel Coding for Efficient and Reliable Cross-Technology Communication
Feb. 16, 2024, 5:43 a.m. | Shumin Yao, Xiaodong Xu, Hao Chen, Yaping Sun, Qinglin Zhao
cs.LG updates on arXiv.org arxiv.org
Abstract: Cross-technology communication (CTC) is a promising technique that enables direct communications among incompatible wireless technologies without needing hardware modification. However, it has not been widely adopted in real-world applications due to its inefficiency and unreliability. To address this issue, this paper proposes a deep joint source-channel coding (DJSCC) scheme to enable efficient and reliable CTC. The proposed scheme builds a neural-network-based encoder and decoder at the sender side and the receiver side, respectively, to achieve …
abstract applications arxiv coding communication communications cs.it cs.lg cs.ni hardware issue math.it paper technologies technology type wireless world
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Business Data Scientist, gTech Ads
@ Google | Mexico City, CDMX, Mexico
Lead, Data Analytics Operations
@ Zocdoc | Pune, Maharashtra, India