{"title":"Iterative MPC for Energy Management and Load Balancing in 5G Heterogeneous Networks","authors":"A. Ornatelli, A. Tortorelli, A. Giuseppi","doi":"10.1109/UEMCON51285.2020.9298113","DOIUrl":null,"url":null,"abstract":"Multi-Access Heterogeneous Networks introduced a step forward in modern communication networks allowing the provision of reliable and efficient broadband services. However, heterogeneous networks imply a burden of complexity in the integration, coordination and QoS management processes thus complicating the satisfaction of users’ requirements. The aim of the present work is to address the above-mentioned issues by developing a mathematical framework for optimizing resource usage in 5G heterogeneous networks. More in detail, the optimization will take into account both the network’s load and energy consumption simultaneously. The proposed approach, based on Model Predictive Control, will be compared with other control strategies for validation and performance comparison.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UEMCON51285.2020.9298113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Multi-Access Heterogeneous Networks introduced a step forward in modern communication networks allowing the provision of reliable and efficient broadband services. However, heterogeneous networks imply a burden of complexity in the integration, coordination and QoS management processes thus complicating the satisfaction of users’ requirements. The aim of the present work is to address the above-mentioned issues by developing a mathematical framework for optimizing resource usage in 5G heterogeneous networks. More in detail, the optimization will take into account both the network’s load and energy consumption simultaneously. The proposed approach, based on Model Predictive Control, will be compared with other control strategies for validation and performance comparison.