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Friday, May 24, 2024
All Day
Presenter: Muhammad Osama Shahid
The NSF AI Institute for Edge Computing (Athena) is pleased to present the next in the Seminar Series by Muhammad Osama Shahid, titled “Enabling Cloud Radio Access Networks for LPWANs Using RL Based Dynamic Compression” on Friday, May 24, 2024, from 12-1pm EST via Zoom https://duke.zoom.us/j/97740995468?pwd=ZFJCWUpGWGtDeXpKelA5Q2xRb1NlQT09
Meeting ID: 977 4099 5468
Passcode: 951110
Abstract: The Cloud Radio Access Network (CRAN) architecture has been proposed as a way of addressing the network throughput and scalability challenges of large-scale LPWANs. CRANs can improve network throughput by coherently combining signals, and scale to multiple channels by implementing the receivers in the cloud. However, in remote LPWAN deployments, a CRAN’s demand for high-backhaul bandwidths can be challenging to meet. Therefore, bandwidth-aware compression of radio samples is needed to reap the benefits of CRANs. We introduce Cloud-LoRa, the first practical CRAN for LoRa (a popular LPWAN technology), that can detect sub-noise signals and perform bandwidth-adaptive compression. In this talk, we will discuss our proposed RL based dynamic compression algorithm to meet the limited and significantly varying backhaul bandwidth in remote locations.
Bio: Muhammad Osama Shahid is a 5th year PhD student at the University of Wisconsin-Madison. His thesis is on the topic of increasing Scalability and throughput of Low Power Wide Area Networks (LPWANs).
Host: Bhuvana Krishnaswamy, Assistant Professor, Department of Electrical and Computer Engineering, University of Wisconsin-Madison
Please contact info-athena@duke.edu if you have any questions or would like to learn more about the Athena Institute. Connect with us @TheAthenaInst and on LinkedIn https://www.linkedin.com/in/the-athena-ai-institute/
