Introduction to the Issue on Machine Learning for Cognition in Radio Communications and Radar

TO BORROW from the inaugural editorial of this Journal,that signal processing is always at the heart of the technol-ogy that differentiates today’s generations from those of the pastis reaffirmed once again by this special issue on Machine Learn-ing for Cognition in Radio Communications and Radar. Machinelearning is the technological disruptor of our time, achievinggroundbreaking success in self-driving cars, gaming and virtualreality, natural language processing and business analytics. Thisspecial issue articulates its impact on signal processing researchin radio communications and radar by showcasing a stunningdiversity of research problems addressed by means of machinelearning. As guest editors of this special issue, we aimed to showthe variety of topics outlined in the call for papers. We werevery pleased by the number and quality of submissions, whichallowed us to select an excellent set of papers representative ofthat diversity. It appears that despite the lack of big data in com-munications and radar, the momentum from the deep learningrevolution has had a spill-over effect, inspiring new and creativeapproaches to signal processing problems in these fields