Open Radio Access Network challenges for Next Generation Mobile Network

被引:7
作者
Aryal, Nischal [1 ,2 ]
Bertin, Emmanuel [1 ,2 ]
Crespi, Noel [2 ]
机构
[1] Orange Innovat, F-14000 Caen, France
[2] Inst Polytech Paris, Telecom SudParis, SAMOVAR, F-91120 Palaiseau, France
来源
2023 26TH CONFERENCE ON INNOVATION IN CLOUDS, INTERNET AND NETWORKS AND WORKSHOPS, ICIN | 2023年
关键词
Disaggregation; Open RAN; ORAN; Challenges; INTELLIGENCE; RAN;
D O I
10.1109/ICIN56760.2023.10073507
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Due to the tightly-coupled hardware and software architecture of existing RAN systems and their non-flexibility, disaggregation of software and hardware can bring many unprecedented opportunities regarding enabling the entrance of multiple small-scale infrastructure providers to enter the RAN market, which creates more competitive and innovative RAN ecosystem. Moreover, mobile network operators (MNOs) will also have the advantage of selecting the services according to their network requirements. Open Radio Access Network (O-RAN) builds a multi-vendor RAN ecosystem and utilizes openness and intelligence to address the complexity of network functionalities, increase development agility, and provide more cost-effective platforms due to softwarization and the avoidance of dedicated hardware. However, O-RAN faces many challenges, such as interoperability, convergence, and AI/ML management which still need to be addressed before its wide deployment. This paper surveys the existing issues in the Open RAN ecosystem and explores existing solutions.
引用
收藏
页数:5
相关论文
共 48 条
[11]   Intelligence and Learning in O-RAN for Data-Driven NextG Cellular Networks [J].
Bonati, Leonardo ;
D'Oro, Salvatore ;
Polese, Michele ;
Basagni, Stefano ;
Melodia, Tommaso .
IEEE COMMUNICATIONS MAGAZINE, 2021, 59 (10) :21-27
[12]   CellOS: Zero-touch Softwarized Open Cellular Networks [J].
Bonati, Leonardo ;
D'Oro, Salvatore ;
Bertizzolo, Lorenzo ;
Demirors, Emrecan ;
Guan, Zhangyu ;
Basagni, Stefano ;
Melodia, Tommaso .
COMPUTER NETWORKS, 2020, 180
[13]   Deep Learning for B5G Open Radio Access Network: Evolution, Survey, Case Studies, and Challenges [J].
Brik, Bouziane ;
Boutiba, Karim ;
Ksentini, Adlen .
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2022, 3 :228-250
[14]   WIP: Impact of AI/ML Model Adaptation on RAN Control Loop Response Time [J].
Chintapalli, Venkatarami Reddy ;
Gudepu, Venkateswarlu ;
Kondepu, Koteswararao ;
Sgambelluri, Andrea ;
Franklin, Antony ;
Tamma, Bheemarjuna Reddy ;
Castoldi, Piero ;
Valcarenghi, Luca .
2022 IEEE 23RD INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (WOWMOM 2022), 2022, :181-184
[15]  
Coronado E., 2022, NOMS 2022 2022 IEEEI, P1
[16]  
D'Oro S, 2022, Arxiv, DOI arXiv:2203.02370
[17]   OrchestRAN: Network Automation through Orchestrated Intelligence in the Open RAN [J].
D'Oro, Salvatore ;
Bonati, Leonardo ;
Polese, Michele ;
Melodia, Tommaso .
IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2022), 2022, :270-279
[18]   Toward Modular and Flexible Open RAN Implementations in 6G Networks: Traffic Steering Use Case and O-RAN xApps [J].
Dryjanski, Marcin ;
Kulacz, Lukasz ;
Kliks, Adrian .
SENSORS, 2021, 21 (24)
[19]   A Column Generation Algorithm for Dedicated-Protection O-RAN VNF Deployment [J].
Duong, Quang Huy ;
Tamim, Ibrahim ;
Jaumard, Brigitte ;
Shami, Abdallah .
2022 INTERNATIONAL WIRELESS COMMUNICATIONS AND MOBILE COMPUTING, IWCMC, 2022, :1206-1211
[20]   From Cloud RAN to Open RAN [J].
Gavrilovska, Liljana ;
Rakovic, Valentin ;
Denkovski, Daniel .
WIRELESS PERSONAL COMMUNICATIONS, 2020, 113 (03) :1523-1539