报告开始:2026年11月21日 13:00(Asia/Kolkata)
报告时间:180min
所在会场:[T] TUTORIAL TALK [T1] TUTORIAL TALK
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Integrated Sensing and Communication (ISAC) is emerging as a foundational capability for 6G systems, enabling wireless networks to go beyond data transmission and actively perceive their environment. By integrating sensing and communication within shared waveforms, spectrum, and hardware, ISAC enables new applications such as localization, environmental awareness, and intelligent connectivity.
This tutorial presents a comprehensive overview of ISAC, combining system-level concepts with practical hardware prototyping workflows. It introduces key architectural principles, where shared RF front ends, antenna arrays, and OFDM-based waveforms support both communication and sensing functions. The session demonstrates how communication signals can be repurposed for sensing by extracting parameters such as range, Doppler, and direction from channel estimates.
Using representative examples, the tutorial covers communication-centric ISAC systems based on MIMO-OFDM designs, radar-centric approaches, and implementations with cellular waveforms. It highlights how these systems can detect and track targets while maintaining communication performance. The tutorial also presents practical workflows for prototyping ISAC systems on SDR platforms, including waveform generation, over-the-air transmission, capture, and post-processing. The tutorial uniquely emphasizes end-to-end workflows from system-level modeling to real-time SDR and FPGA deployment, demonstrated through practical UAV detection scenarios.
Saumya Chaturvedi is an Engineer in the Education Team at MathWorks (2025–present). She holds a PhD in Wireless Communications from IIIT Delhi, along with an M.Tech. in Microwaves from NIT Delhi and a B.E. from UIT RGPV Bhopal. Her technical expertise lies in wireless communication systems, with a focus on multiple access and resource allocation techniques
Anand is a Senior Engineer on the Education Team at MathWorks, Bangalore, where he has been contributing since August 2020. He collaborates with academic institutions and educators to enhance their curriculum and research initiatives. Before joining MathWorks, Anand completed his Ph.D. in neuromorphic computing applications at IIT Kharagpur (2015–2020). He also holds an M. Tech. in VLSI Design and Embedded Systems from NIT Rourkela (2012–2014) and a B.Tech. in Electronics and Communication Engineering from Techno India College of Technology (2008–2012). Anand has authored and co-authored research articles in various journals and conferences. His interests focus on digital VLSI, HDL code generation workflows, artificial intelligence applications.
11月20日
2026
11月22日
2026
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