BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Montevideo BEGIN:DAYLIGHT DTSTART:20380119T001407 TZOFFSETFROM:-0300 TZOFFSETTO:-0300 RRULE:FREQ=YEARLY;BYDAY=3TU;BYMONTH=1 TZNAME:-03 END:DAYLIGHT BEGIN:STANDARD DTSTART:20150308T010000 TZOFFSETFROM:-0200 TZOFFSETTO:-0300 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:-03 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260721T150522Z UID:389C5921-B6D8-4D9C-AA75-7A5C3AFED8FF DTSTART;TZID=America/Montevideo:20260717T150000 DTEND;TZID=America/Montevideo:20260717T170000 DESCRIPTION:In this talk\, we review recent work on edge computing and comm unications as a key enabler for future wireless networks. In particular\, we present samples of our work on proactive caching\, decentralized coded caching\, cache-aided MIMO networks and federated learning over blockchain networks.\n\nIn the first part of the talk\, we shed light on a sample of our work on edge content caching. We present performance limits for decen tralized coded caching in Fog Radio Access Networks with focus on the norm alized delivery time (NDT) performance metric. Afterwards\, we extend our discussion to cache-aided MIMO networks where we generalize prior studies to the case of arbitrary number of transmitters\, receivers and antennas. We establish fundamental limits characterizing the relative contributions of the spatial multiplexing gain vs. the coded caching gain\, with respect to reducing the delivery latency.\n\nIn the second part of the talk\, we shift our focus to edge intelligence\, in particular\, federated learning over blockchain networks. Motivated by the wide prevalence of decentralize d data\, we propose a novel federated learning framework with no parameter service\, yet\, relying on the distributed ledger security infrastructure of blockchains. This is achieved by employing “validators” who evalua te the quality of the “trainer” model updates through a validation dat aset and byzantine fault tolerance. This work opens ample room for future research through revealing interesting insights and fundamental trade-offs .\n\nCo-sponsored by: UTEC Prof. Diego Quiroga\n\nSpeaker(s): Tamer Elbatt \, \n\nBldg: UTEC Fray Bentos.\, Barrio Anglo\, Fray Bentos\, Rio Negro\, Uruguay\, Virtual: https://events.vtools.ieee.org/m/566697 LOCATION:Bldg: UTEC Fray Bentos.\, Barrio Anglo\, Fray Bentos\, Rio Negro\ , Uruguay\, Virtual: https://events.vtools.ieee.org/m/566697 ORGANIZER:joseluis.rodriguez@ieee.org SEQUENCE:186 SUMMARY:Edge Computing and Communications for NextG: Fundamental Limits and Applications URL;VALUE=URI:https://events.vtools.ieee.org/m/566697 X-ALT-DESC:Description: <br /><p>&nbsp\;</p>\n<p class="MsoNormal" style="t ext-align: justify\;">In this talk\, we review<span style="mso-ansi-langua ge: EN-US\;"> </span>recent work <span style="mso-ansi-language: EN-US\;"> on edge computing and communications as a key enabler for future wireless networks</span>. In particular\, we <span style="mso-ansi-language: EN-US\ ;">present</span> sample<span style="mso-ansi-language: EN-US\;">s</span> of our work on <span style="mso-ansi-language: EN-US\;">proactive caching\ , decentralized coded caching\, cache-aided MIMO networks and federated le arning over blockchain networks.</span></p>\n<p class="MsoNormal" style="t ext-align: justify\;"><span style="mso-ansi-language: EN-US\;">&nbsp\;</sp an></p>\n<p class="MsoNormal" style="text-align: justify\;">In the first p art of the talk\, we shed light on <span style="mso-ansi-language: EN-US\; ">a </span>sample of our work<span style="mso-ansi-language: EN-US\;"> on edge content caching. We present performance limits for decentralized code d caching in Fog Radio Access Networks with focus on </span><span style="m so-bidi-font-size: 11.0pt\; mso-bidi-font-family: Calibri\; mso-bidi-theme -font: minor-latin\;">the normalized delivery time (NDT)</span><span style ="mso-bidi-font-size: 11.0pt\; mso-bidi-font-family: Calibri\; mso-bidi-th eme-font: minor-latin\; mso-ansi-language: EN-US\;"> performance metric</s pan><span style="mso-ansi-language: EN-US\;">. Afterwards\, we extend our discussion to cache-aided MIMO networks where we generalize prior studies to the case of arbitrary number of transmitters\, receivers and antennas. We establish fundamental limits characterizing the relative contributions of the spatial multiplexing gain vs. the coded caching gain\, with respect to reducing the delivery latency. </span></p>\n<p class="MsoNormal" style ="text-align: justify\;">&nbsp\;</p>\n<p class="MsoNormal" style="text-ali gn: justify\;">In the second part of the talk\, we shift <span style="mso- ansi-language: EN-US\;">our focus</span> to <span style="mso-ansi-language : EN-US\;">edge intelligence\, in particular\, federated learning over blo ckchain networks</span>. <span style="mso-ansi-language: EN-US\;">Motivate d by the wide prevalence of decentralized data\, we propose a novel federa ted learning framework with no parameter service\, yet\, relying on the di stributed ledger security infrastructure of blockchains. This is achieved by employing &ldquo\;validators&rdquo\; who evaluate the quality of the &l dquo\;trainer&rdquo\; model updates through a validation dataset and byzan tine fault tolerance. This work opens ample room for future research throu gh revealing interesting insights and fundamental trade-offs. <span style= "mso-spacerun: yes\;">&nbsp\;</span></span></p>\n<p class="MsoNormal">&nbs p\;</p> END:VEVENT END:VCALENDAR