Event Date
Abstract
We overview key enabling technologies and new applications for the 6G era (the 2030s). One of the most important enablers will be deep learning, a fast advancing technology, which can unlock previously hidden system-level gains, particularly by efficiently learning custom site- specific communication techniques that are optimally adapted for each cell-site. I will present a short summary of some of my group’s recent discoveries and technologies based on deep learning (DL) that demonstrate a large potential impact in 6G. The first is a novel and practical approach for beam alignment in millimeter wave and THz bands that can achieve a phenomenal speed up — at least 10x and in some cases approaching 1000x — by sensing and exploiting unique aspects of the environment. The second is a novel methodology for downlink precoding and uplink feedback for upper midband (7-15 GHz) spectrum, that can be used for both SU-MIMO and MU-MIMO. The UEs learn near-optimal feedback patterns and the BSs learn near-optimal precoders directly from that feedback. The technique is trained and tested using Nokia’s ray tracing based channel model for 7 GHz channels. The third is a site-specific multicell optimization that rapidly learns near-optimal global settings for each base stations antenna arrays, a problem that is completely intractable using conventional techniques. It is trained and tested on AT&T’s commercial simulation platform and shows at least 2x gain in both coverage and capacity metrics relative to typical settings.
Bio
Jeffrey Andrews is the Truchard Family Endowed Chair in Engineering at the University of Texas at Austin where is Director of 6G@UT. He received the B.S. in Engineering with High Distinction from Harvey Mudd College, and the M.S. and Ph.D. in Electrical Engineering from Stanford University. Dr. Andrews is an IEEE Fellow and ISI Highly Cited Researcher and has been co-recipient of 15 best paper awards as well as the 2015 Terman Award, the NSF CAREER Award, the 2021 Gordon Lepley Memorial Teaching Award, the 2021 IEEE ComSoc Joe LoCicero Service Award, the IEEE ComSoc Wireless Communications Technical Committee Recognition Award, and the 2019 IEEE Kiyo Tomiyasu technical field award. His former students include five IEEE Fellows, 12 professors at top universities in the USA, Asia, and Europe, and industry leaders on LTE and 5G systems, on which they collectively hold over one thousand US patents
Zoom Information
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https://ucdavis.zoom.us/j/92568906773?pwd=ZW5DTkV2cWQ1ejZEakJRc0w0UmN3QT09
Meeting ID: 925 6890 6773
Passcode: 476800