A paper co-authored by Dr. Marco Cominelli and Prof. Francesco Gringoli of the Department of Information Engineering won the Best Paper Award at the prestigious ACM MobiHoc 2023 conference held in Washington DC, USA, last October. The paper resulted from a fruitful collaboration between the University of Brescia, Princeton University (USA), and IMDEA Networks (Spain).
The paper, titled “Scalable Multi-Modal Learning for Cross-Link Channel Prediction in Massive IoT Networks,” proposes a novel technique to address the increasing demand for efficient channel usage in massive IoT networks. In particular, the work demonstrates how it is possible to exploit existing Wi-Fi transmissions to reduce the overhead due to channel estimation and increase the throughput in ultra-dense IoT networks based on IEEE 802.11ax
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