{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T17:07:48Z","timestamp":1774631268648,"version":"3.50.1"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"U.S. National Science Foundation","doi-asserted-by":"publisher","award":["CCF-0939370"],"award-info":[{"award-number":["CCF-0939370"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"U.S. National Science Foundation","doi-asserted-by":"publisher","award":["CCF-1908308"],"award-info":[{"award-number":["CCF-1908308"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000781","name":"European Research Council (ERC) Starting Grant BEACON","doi-asserted-by":"publisher","award":["677854"],"award-info":[{"award-number":["677854"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"U.K. EPSRC","doi-asserted-by":"publisher","award":["EP\/T023600\/1"],"award-info":[{"award-number":["EP\/T023600\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Wireless Commun."],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/twc.2021.3103874","type":"journal-article","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T20:51:00Z","timestamp":1629233460000},"page":"1422-1437","source":"Crossref","is-referenced-by-count":73,"title":["Convergence of Federated Learning Over a Noisy Downlink"],"prefix":"10.1109","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7343-6628","authenticated-orcid":false,"given":"Mohammad Mohammadi","family":"Amiri","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, ~USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7725-395X","authenticated-orcid":false,"given":"Deniz","family":"Gunduz","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, ~USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5308-5250","authenticated-orcid":false,"given":"Sanjeev R.","family":"Kulkarni","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Imperial College London, London, U.K"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2062-131X","authenticated-orcid":false,"given":"H. Vincent","family":"Poor","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, ~USA"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Federated learning: Strategies for improving communication efficiency","volume-title":"Proc. Adv. Neural Inf. Proc. Syst.","author":"Konecny"},{"key":"ref2","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref3","volume-title":"Federated Learning: Collaborative Machine Learning Without Centralized Training Data","author":"McMahan","year":"2017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3389\/fams.2018.00062"},{"key":"ref5","article-title":"Federated multi-task learning","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Smith"},{"key":"ref6","article-title":"Federated optimization: Distributed optimization beyond the datacenter","author":"Kone\u010dn\u00fd","year":"2015","journal-title":"arXiv:1511.03575"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761315"},{"key":"ref8","article-title":"Federated learning with non-IID data","author":"Zhao","year":"2018","journal-title":"arXiv:1806.00582"},{"key":"ref9","article-title":"On the convergence of FedAvg on non-IID data","author":"Li","year":"2019","journal-title":"arXiv:1907.02189"},{"key":"ref10","article-title":"COLA: Decentralized linear learning","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"He"},{"key":"ref11","article-title":"Agnostic federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Mohri"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.2000394"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.2981904"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2946245"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.2989580"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SPAWC.2019.8815402"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.2974748"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2961673"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3002988"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/GlobalSIP45357.2019.8969185"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/GlobalSIP45357.2019.8969185"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3038407"},{"key":"ref23","article-title":"Communication efficient federated learning over multiple access channels","author":"Chang","year":"2020","journal-title":"arXiv:2001.08737"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3039309"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053740"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICC40277.2020.9149138"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2019.2944169"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3126078"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT44484.2020.9173960"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3036971"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3024629"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2020.3035770"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3052681"},{"key":"ref34","article-title":"Federated learning with quantized global model updates","author":"Amiri","year":"2020","journal-title":"arXiv:2006.10672"},{"key":"ref35","article-title":"DoubleSqueeze: Parallel stochastic gradient descent with double-pass error-compensated compression","volume-title":"Proc. Mach. Learn. Res.","author":"Tang"},{"key":"ref36","article-title":"Expanding the reach of federated learning by reducing client resource requirements","author":"Caldas","year":"2018","journal-title":"arXiv:1812.07210"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053448"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2008.921678"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1155\/2010\/172013"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2007.904996"},{"key":"ref41","first-page":"1709","article-title":"QSGD: Communication-efficient SGD via randomized quantization and encoding","volume-title":"Proc. NIPS","author":"Alistarh"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1137\/140961134"},{"key":"ref43","volume-title":"The MNIST Database of Handwritten Digits","author":"LeCun","year":"1998"},{"key":"ref44","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"}],"container-title":["IEEE Transactions on Wireless Communications"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/7693\/9731098\/9515709-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7693\/9731098\/09515709.pdf?arnumber=9515709","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T23:01:05Z","timestamp":1705014065000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9515709\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":44,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/twc.2021.3103874","relation":{},"ISSN":["1536-1276","1558-2248"],"issn-type":[{"value":"1536-1276","type":"print"},{"value":"1558-2248","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}