{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T16:19:37Z","timestamp":1778948377602,"version":"3.51.4"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tmc.2021.3107458","type":"journal-article","created":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T21:15:44Z","timestamp":1630358144000},"page":"1-1","source":"Crossref","is-referenced-by-count":28,"title":["Mobility Load Management in Cellular Networks: A Deep Reinforcement Learning Approach"],"prefix":"10.1109","author":[{"given":"Ghada","family":"Alsuhli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karim","family":"Banawan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kareem","family":"Attiah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayman","family":"Elezabi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karim","family":"Seddik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayman","family":"Gaber","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Zaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasser","family":"Gadallah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CCNC46108.2020.9045699"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/9781118399439"},{"key":"ref4","volume-title":"Reinforcement Learning: An Introduction","author":"Sutton","year":"2018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2018.8636075"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"ref7","first-page":"4294","article-title":"Learning values across many orders of magnitude","volume-title":"Proc. 30th Int. Conf. Neural Inf. Process. Syst.","author":"Guez"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.32657\/10356\/90191"},{"key":"ref9","article-title":"Addressing function approximation error in actor-critic methods","author":"Fujimoto","year":"2018"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2068897.2068948"},{"key":"ref11","article-title":"Recent development and applications of SUMO-Simulation of Urban MObility","volume":"5","author":"Krajzewicz","year":"2012"},{"key":"ref12","article-title":"Paper source code","author":"Alsuhli","year":"2020"},{"issue":"6","key":"ref13","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1109\/JSAC.2014.2328098","article-title":"What will 5G be?","volume":"32","author":"Andrews","year":"2014","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/VETECS.2010.5493656"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC.2013.6666500"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2935010"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/LATINCOM.2015.7430131"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2012.2234156"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2019.2922961"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2959185"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2016.2522080"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761343"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2017.2727878"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2017.2769644"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2878435"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2019.101913"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.23919\/JCIN.2019.8917870"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2916583"},{"key":"ref29","article-title":"LTE; Evolved universal terrestrial radio access (E-UTRA), user equipment (UE) procedures in idle mode","volume-title":"ETSI, Sophia Antipolis, France","year":"2019"},{"key":"ref30","article-title":"LTE; Evolved universal terrestrial radio access (E-UTRA), physical layer procedures","volume-title":"ETSI, Sophia Antipolis, France","year":"2017"},{"key":"ref31","article-title":"3rd generation partnership project; Technical Specification Group Services and System Aspects; Telecommunication management; Study on NM Centralized Coverage and Capacity Optimization (CCO) SON Function (Release 12)","year":"2012"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2977374"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-01585-4"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(94)00012-P"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.23919\/TMA.2019.8784522"},{"key":"ref37","article-title":"Determining network congestion based on target user throughput","author":"Sung","year":"2018"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1002\/dac.4147"},{"key":"ref39","first-page":"3","article-title":"An introduction to deep reinforcement learning","volume":"11","author":"Fran","year":"2018","journal-title":"Found. Trends Mach. Learn."},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1201\/9781351006620-6"},{"key":"ref41","first-page":"756","article-title":"Learning classifiers when the training data is not IID","volume-title":"Proc. 20th Int. Joint Conf. Artif. Intell.","author":"Dundar"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2012.2218595"},{"issue":"14","key":"ref44","article-title":"Network simulations with the ns-3 simulator","volume":"14","author":"Henderson","year":"2008","journal-title":"SIGCOMM Demonstration"},{"key":"ref45","article-title":"ns3-gym: Extending OpenAI gym for networking research","author":"Gawlowicz","year":"2018"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1201\/9781315281896-74"},{"key":"ref47","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","author":"Haarnoja","year":"2018","journal-title":""},{"key":"ref48","article-title":"Reinforcement learning with deep energy-based policies","author":"Haarnoja","year":"2017"},{"key":"ref49","article-title":"Diversity actor-critic: Sample-aware entropy regularization for sample-efficient exploration","author":"Han","year":"2020","journal-title":""},{"key":"ref50","article-title":"Soft actor-critic algorithms and applications","author":"Haarnoja","year":"2018"},{"key":"ref51","article-title":"Off-policy maximum entropy reinforcement learning: Soft actor-critic with advantage weighted mixture policy (SAC-AWMP)","author":"Hou","year":"2020"},{"key":"ref52","article-title":"Stable baselines","author":"Hill","year":"2018"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2743240"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7755\/4358975\/09525270.pdf?arnumber=9525270","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T22:22:04Z","timestamp":1705011724000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9525270\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/tmc.2021.3107458","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"value":"1536-1233","type":"print"},{"value":"1558-0660","type":"electronic"},{"value":"2161-9875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}