BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20230312T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20231105T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20230724T143434Z UID:A15C519A-EC2C-4910-98D5-035816CBD60C DTSTART;TZID=America/New_York:20230720T180000 DTEND;TZID=America/New_York:20230720T200000 DESCRIPTION:The millimeter-wave (mm-Wave) massive multiple-input multiple-o utput (MIMO) communications employ hybrid analog-digital beamforming archi tectures to reduce the cost-power-size-hardware overheads arising from the use of extremely large arrays at this band. Lately\, there is also a grad ual push to move from the millimeter-wave (mmWave) to Terahertz (THz) freq uencies for short-range communications and radar applications to exploit v ery wide THz bandwidths. At THz\, ultramassive MIMO array is an enabling t echnology to exploit ultrawide bandwidth while employing thousands of ante nnas. The design of the hybrid beamforming techniques requires the solutio n to difficult nonconvex optimization problems that involve a common perfo rmance metric as a cost function and several constraints related to the em ployed communication regime and the adopted architecture of the hybrid sys tem(s). There is no standard methodology for solving such problems and usu ally\, the derivation of an efficient solution is a very challenging task. Since optimization-based approaches suffer from high computational comple xity and their performance strongly relies on the perfect channel conditio n\, we introduce deep learning (DL) techniques that provide robust perform ance while designing a hybrid beamformer. In this talk\, the audience will learn about applying DL to various aspects of hybrid beamforming includin g channel estimation\, antenna selection\, wideband beamforming\, and spat ial modulation. In addition\, we will examine these concepts in the contex t of joint radar-communications and intelligent-surfaces-aided architectur es.\n\nCo-sponsored by: Prasad Atluri\, Chair Communication Soc\n\nSpeaker (s): Dr. Mishra\, \n\nAgenda: \nArrive in township meeting room (within Ho lmdel library) by 5.45pm\n\nSet up talk in the meeting room and also set u p Webex session 5:50pm\n\nBegin talk (6PM): Deep learning for massive MIMO hybrid beamforming\n\nConclude talk (7PM) and begin Q & A session\n\n7:30 PM close of event - all those who attend "in person" will join speaker for dinner at local restaurant\n\n----\n\nDistinguished talk "Deep learning f or massive MIMO hybrid beamforming"\nThursday\, July 20\, 2023\n6:00 PM | (UTC-04:00) Eastern Time (US & Canada) | 2 hrs\n\n[Join WebEx meeting](htt ps://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m776fe215adfd6bd224ec6 f42b76383fa)\n\nhttps://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m77 6fe215adfd6bd224ec6f42b76383fa\n\nMeeting number: 2538 459 6318\nMeeting p assword: qRZuGXkZ555\n\nJoin from a video system or application\n\nDial 25 384596318@ieeemeetings.webex.com\nYou can also dial 173.243.2.68 and enter your meeting number.\nTo dial from an IEEE Video Conference System: *1 25 38 459 6318\n\nTap to join from a mobile device (attendees only)\n\n[+1-41 5-655-0002\,\,25384596318##](tel:%2B1-415-655-0002\,\,*01*25384596318%23%2 3*01*) United States Toll\n[1-855-282-6330\,\,25384596318##](tel:1-855-282 -6330\,\,*01*25384596318%23%23*01*) United States Toll Free\n\nRoom: Towns hip meeting room\, Bldg: Bell Works\, 101 Crawfords Corner Road\, Holmdel\ , New Jersey\, United States\, 07733 LOCATION:Room: Township meeting room\, Bldg: Bell Works\, 101 Crawfords Cor ner Road\, Holmdel\, New Jersey\, United States\, 07733 ORGANIZER:raghunandan@ieee.org SEQUENCE:22 SUMMARY:Deep learning for massive MIMO hybrid beamforming - Hybrid event URL;VALUE=URI:https://events.vtools.ieee.org/m/361614 X-ALT-DESC:Description: <br /><p>The millimeter-wave (mm-Wave) massive mult iple-input multiple-output (MIMO) communications employ hybrid analog-digi tal beamforming architectures to reduce the cost-power-size-hardware overh eads arising from the use of extremely large arrays at this band. Lately\, there is also a gradual push to move from the millimeter-wave (mmWave) to Terahertz (THz) frequencies for short-range communications and radar appl ications to exploit very wide THz bandwidths. At THz\, ultramassive MIMO a rray is an enabling technology to exploit ultrawide bandwidth while employ ing thousands of antennas. The design of the hybrid beamforming techniques requires the solution to difficult nonconvex optimization problems that i nvolve a common performance metric as a cost function and several constrai nts related to the employed communication regime and the adopted architect ure of the hybrid system(s). There is no standard methodology for solving such problems and usually\, the derivation of an efficient solution is a v ery challenging task. Since optimization-based approaches suffer from high computational complexity and their performance strongly relies on the per fect channel condition\, we introduce deep learning (DL) techniques that p rovide robust performance while designing a hybrid beamformer. In this tal k\, the audience will learn about applying DL to various aspects of hybrid beamforming including channel estimation\, antenna selection\, wideband b eamforming\, and spatial modulation. In addition\, we will examine these c oncepts in the context of joint radar-communications and intelligent-surfa ces-aided architectures.</p><br /><br />Agenda: <br /><p>Arrive in townshi p meeting room (within Holmdel library) by 5.45pm</p>\n<p>Set up talk in t he meeting room and also set up Webex session 5:50pm</p>\n<p>Begin talk (6 PM): Deep learning for massive MIMO hybrid beamforming</p>\n<p>Conclude ta lk (7PM) and begin Q &amp\; A session</p>\n<p>7:30PM close of event - all those who attend "in person" will join speaker for dinner at local restaur ant</p>\n<p>----</p>\n<table style="font-weight: 400\;" width="100%">\n<tb ody>\n<tr>\n<td><strong>Distinguished talk "Deep learning for massive MIMO hybrid beamforming"</strong></td>\n</tr>\n<tr>\n<td>Thursday\, July 20\, 2023</td>\n</tr>\n<tr>\n<td>6:00 PM&nbsp\;&nbsp\;|&nbsp\;&nbsp\;(UTC-04:00 ) Eastern Time (US &amp\; Canada)&nbsp\;&nbsp\;|&nbsp\;&nbsp\;2 hrs</td>\n </tr>\n</tbody>\n</table>\n<table style="font-weight: 400\;">\n<tbody>\n<t r>\n<td>&nbsp\;</td>\n</tr>\n</tbody>\n</table>\n<table style="font-weight : 400\;">\n<tbody>\n<tr>\n<td><a href="https://ieeemeetings.webex.com/ieee meetings/j.php?MTID=m776fe215adfd6bd224ec6f42b76383fa" data-saferedirectur l="https://www.google.com/url?q=https://ieeemeetings.webex.com/ieeemeeting s/j.php?MTID%3Dm776fe215adfd6bd224ec6f42b76383fa&amp\;source=gmail&amp\;us t=1684596490213000&amp\;usg=AOvVaw1qbhvqVpDkCkyZsSQuz-zr"><strong>Join Web Ex meeting</strong></a></td>\n</tr>\n</tbody>\n</table>\n<p style="font-we ight: 400\;"><br /><a href="https://ieeemeetings.webex.com/ieeemeetings/j. php?MTID=m776fe215adfd6bd224ec6f42b76383fa" data-saferedirecturl="https:// www.google.com/url?q=https://ieeemeetings.webex.com/ieeemeetings/j.php?MTI D%3Dm776fe215adfd6bd224ec6f42b76383fa&amp\;source=gmail&amp\;ust=168459649 0213000&amp\;usg=AOvVaw1qbhvqVpDkCkyZsSQuz-zr">https://ieeemeetings.webex. com/ieeemeetings/j.php?MTID=m776fe215adfd6bd224ec6f42b76383fa</a><br /><br /></p>\n<table style="font-weight: 400\;">\n<tbody>\n<tr>\n<td>Meeting nu mber:</td>\n<td>2538 459 6318</td>\n</tr>\n<tr>\n<td>Meeting password:</td >\n<td>qRZuGXkZ555</td>\n</tr>\n</tbody>\n</table>\n<p style="font-weight: 400\;">&nbsp\;</p>\n<table style="font-weight: 400\;">\n<tbody>\n<tr>\n<t d>&nbsp\;</td>\n</tr>\n</tbody>\n</table>\n<p>Join from a video system or application</p>\n<table style="font-weight: 400\;">\n<tbody>\n<tr>\n<td>Di al&nbsp\;25384596318@ieeemeetings.webex.com</td>\n</tr>\n<tr>\n<td>You can also dial 173.243.2.68 and enter your meeting number.</td>\n</tr>\n</tbod y>\n</table>\n<p style="font-weight: 400\;">To dial from an IEEE Video Con ference System:&nbsp\;<strong>*1 2538 459 6318</strong><br /><br /></p>\n< p>Tap to join from a mobile device (attendees only)</p>\n<table style="fon t-weight: 400\;">\n<tbody>\n<tr>\n<td><a href="tel:%2B1-415-655-0002\,\,*0 1*25384596318%23%23*01*">+1-415-655-0002\,\,25384596318##</a>&nbsp\;United States Toll</td>\n</tr>\n<tr>\n<td><a href="tel:1-855-282-6330\,\,*01*253 84596318%23%23*01*">1-855-282-6330\,\,25384596318##</a>&nbsp\;United State s Toll Free</td>\n</tr>\n</tbody>\n</table> END:VEVENT END:VCALENDAR