id:"swepub:oai:DiVA.org:liu-164860"
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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 03672naa a2200361 4500 | |
| 001 | oai:DiVA.org:liu-164860 | |
| 003 | SwePub | |
| 008 | 200330s2020 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1648602 URI |
| 024 | 7 | a https://doi.org/10.1109/MWC.001.19002922 DOI |
| 040 | a (SwePub)liu | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a ref2 swepub-contenttype |
| 072 | 7 | a art2 swepub-publicationtype |
| 100 | 1 | a Wang, Cheng-Xiangu Southeast Univ, Peoples R China; Purple Mt Labs, Peoples R China4 aut |
| 245 | 1 0 | a Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges |
| 264 | 1 | b IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC,c 2020 |
| 338 | a electronic2 rdacarrier | |
| 500 | a Funding Agencies|National Key R&D Program of China [2018YFB1801101]; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China [61960206006]; High Level Innovation and Entrepreneurial Talent Introduction Program in Jiangsu; Research Fund of National Mobile Communications Research Laboratory, Southeast University [2020B01]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [2242019R30001]; EU H2020 RISE TESTBED2 project [872172] | |
| 520 | a 5G wireless communication networks are currently being deployed, and B5G networks are expected to be developed over the next decade. AI technologies and, in particular, ML have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts of data that need to be dealt with in B5G. This article studies how AI and ML can be leveraged for the design and operation of B5G networks. We first provide a comprehensive survey of recent advances and future challenges that result from bringing AI/ML technologies into B5G wireless networks. Our survey touches on different aspects of wireless network design and optimization, including channel measurements, modeling, and estimation, physical layer research, and network management and optimization. Then ML algorithms and applications to B5G networks are reviewed, followed by an overview of standard developments of applying AI/ML algorithms to B5G networks. We conclude this study with future challenges on applying AI/ML to B5G networks. | |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Kommunikationssystem0 (SwePub)202032 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Communication Systems0 (SwePub)202032 hsv//eng |
| 653 | a Artificial intelligence; Channel estimation; Massive MIMO; 5G mobile communication; Loss measurement; Wireless networks | |
| 700 | 1 | a Di Renzo, Marcou Univ Paris Saclay, France4 aut |
| 700 | 1 | a Stanczak, Slawomiru Heinrich Hertz Inst Nachrichtentech Berlin GmbH, Germany; Tech Univ Berlin, Germany4 aut |
| 700 | 1 | a Wang, Senu Heriot Watt Univ, Scotland4 aut |
| 700 | 1 | a Larsson, Erik Gu Linköpings universitet,Kommunikationssystem,Tekniska fakulteten4 aut0 (Swepub:liu)erila39 |
| 710 | 2 | a Southeast Univ, Peoples R China; Purple Mt Labs, Peoples R Chinab Univ Paris Saclay, France4 org |
| 773 | 0 | t IEEE wireless communicationsd : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCg 27:1, s. 16-23q 27:1<16-23x 1536-1284x 1558-0687 |
| 856 | 4 | u https://liu.diva-portal.org/smash/get/diva2:1417686/FULLTEXT01.pdfx primaryx Raw objecty fulltext:postprint |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-164860 |
| 856 | 4 8 | u https://doi.org/10.1109/MWC.001.1900292 |
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