Improving Communication Systems with Clustering Algorithms | Bill Gavin, University of Sheffield
Bill Gavin is a second year PhD student at the University of Sheffield, his areas of interest are applying machine learning systems to communications systems and hardware acceleration of machine learning algorithms on FPGA platforms. Bill is attending the SAI conference to present his efficient RF modulation classifier which utilises an optimised DBSCAN clustering algorithm.
In this video Bill discusses his groundbreaking research using clustering algorithms. In his paper, he explores the application of the DBSCAN algorithm to modulation classification, aiming to enhance existing results in the literature. Discover how Bill's work achieves an impressive accuracy increase over time series methods like LSTM, maintaining 100% accuracy above 16 DPSK. These findings have significant implications for future communication systems, potentially benefiting upcoming generations like 6G, 7G, and 8G.
As Bill looks forward to exchanging ideas and collaborating with new acquaintances, he emphasizes the value of networking at conferences. Don't miss this informative interview, which sheds light on the potential of clustering algorithms in revolutionizing communication systems.
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