Channel measurements and models for 6G: current status and future outlook

With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high data rates and low latency for future services. A wireless propagation channel is the transmission medium to transfer information between the...

Full description

Saved in:

Bibliographic Details
Published in	Frontiers of information technology & electronic engineering Vol. 21; no. 1; pp. 39 - 61
Main Authors	Zhang, Jian-hua, Tang, Pan, Yu, Li, Jiang, Tao, Tian, Lei
Format	Journal Article
Language	English
Published	Hangzhou Zhejiang University Press 01.01.2020 Springer Nature B.V State Key Lab of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
Subjects	6G mobile communication Commercialization Communications Engineering Communications networks Computer Hardware Computer Science Computer Systems Organization and Communication Networks Electrical Engineering Electronics and Microelectronics Industrial applications Industrial Internet of Things Instrumentation Internet of Things Machine learning Network latency Networks New technology Propagation R&D Research & development Review Technology Trends Wireless communication systems Wireless communications Machine learning Channel measurements Sixth generation Terahertz Channel models TN929.5 Space-air-ground integrated network Industrial Internet of Things
Online Access	Get full text
ISSN	2095-9184 2095-9230
DOI	10.1631/FITEE.1900450

Cover

Abstract	With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high data rates and low latency for future services. A wireless propagation channel is the transmission medium to transfer information between the transmitter and the receiver. Moreover, channel properties determine the ultimate performance limit of wireless communication systems. Thus, conducting channel research is a prerequisite to designing 6G wireless communication systems. In this paper, we first introduce several emerging technologies and applications for 6G, such as terahertz communication, industrial Internet of Things, space-air-ground integrated network, and machine learning, and point out the developing trends of 6G channel models. Then, we give a review of channel measurements and models for the technologies and applications. Finally, the outlook for 6G channel measurements and models is discussed.
AbstractList	With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high data rates and low latency for future services. A wireless propagation channel is the transmission medium to transfer information between the transmitter and the receiver. Moreover, channel properties determine the ultimate performance limit of wireless communication systems. Thus, conducting channel research is a prerequisite to designing 6G wireless communication systems. In this paper, we first introduce several emerging technologies and applications for 6G, such as terahertz communication, industrial Internet of Things, space-air-ground integrated network, and machine learning, and point out the developing trends of 6G channel models. Then, we give a review of channel measurements and models for the technologies and applications. Finally, the outlook for 6G channel measurements and models is discussed. TN929.5; With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high data rates and low latency for future services. A wireless propagation channel is the transmission medium to transfer information between the transmitter and the receiver.Moreover, channel properties determine the ultimate performance limit of wireless communication systems. Thus, conducting channel research is a prerequisite to designing 6G wireless communication systems. In this paper, we first introduce several emerging technologies and applications for 6G, such as terahertz communication, industrial Internet of Things, space-air-ground integrated network, and machine learning, and point out the developing trends of 6G channel models. Then, we give a review of channel measurements and models for the technologies and applications. Finally, the outlook for 6G channel measurements and models is discussed.
Author	Tang, Pan Yu, Li Jiang, Tao Zhang, Jian-hua Tian, Lei
AuthorAffiliation	State Key Lab of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
AuthorAffiliation_xml	– name: State Key Lab of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
Author_xml	– sequence: 1 givenname: Jian-hua orcidid: 0000-0002-6492-3846 surname: Zhang fullname: Zhang, Jian-hua organization: State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications – sequence: 2 givenname: Pan orcidid: 0000-0003-0432-7361 surname: Tang fullname: Tang, Pan email: tangpan27@bupt.edu.cn organization: State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications – sequence: 3 givenname: Li surname: Yu fullname: Yu, Li organization: State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications – sequence: 4 givenname: Tao surname: Jiang fullname: Jiang, Tao organization: State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications – sequence: 5 givenname: Lei surname: Tian fullname: Tian, Lei organization: State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications
BookMark	eNp1kM1LAzEQxYNUsNYevS94E7bmYz8Sb1LaWhC81HNIN0ndupvUJIvVv97oVgqipxmY35t5887BwFijALhEcIIKgm7my9VsNkEMwiyHJ2CIIctThgkc_PSIZmdg7P0WQogKxEpGh2A5fRbGqCZplfCdU60ywSfCyKS1UjU-0dYlxeI2qTrn4izxQYSuJ3QXoiKxXWisfbkAp1o0Xo0PdQSe5rPV9D59eFwsp3cPaUUIC6lkCEmZQSHZOkdK0rygTEuSqRIjCnU0hvOqYkyRksK1xJkQIqeaIi0zqTAZget-75swWpgN39rOmXiRf2zlfr-uuMIQxxchzCN81cM7Z1875cORxjGQEhe4QJEiPVU5671Tmld1fLO2JjhRNxxB_pUx_86YHzKOqvSXaufqVrj3f_lJz_vImY1yRy9_Cz4BBnaM_A
CitedBy_id	crossref_primary_10_3390_electronics11050820 crossref_primary_10_23919_ICN_2024_0019 crossref_primary_10_1109_COMST_2022_3182539 crossref_primary_10_1049_iet_com_2020_0531 crossref_primary_10_1109_LWC_2024_3397839 crossref_primary_10_1109_JSAC_2024_3492720 crossref_primary_10_1007_s10776_021_00546_3 crossref_primary_10_1631_FITEE_2200290 crossref_primary_10_1109_COMST_2022_3205505 crossref_primary_10_1016_j_compeleceng_2023_108581 crossref_primary_10_1109_MCOM_001_2200486 crossref_primary_10_1109_LWC_2022_3192516 crossref_primary_10_1109_LWC_2023_3262691 crossref_primary_10_1029_2021RS007385 crossref_primary_10_1109_ACCESS_2021_3069707 crossref_primary_10_1109_TAP_2022_3218759 crossref_primary_10_1109_TITS_2024_3465014 crossref_primary_10_1007_s11277_024_11349_z crossref_primary_10_1109_COMST_2022_3184049 crossref_primary_10_1016_j_ijleo_2021_166415 crossref_primary_10_1109_JIOT_2020_3048992 crossref_primary_10_3390_photonics9040228 crossref_primary_10_1002_mop_33662 crossref_primary_10_3390_ma15186364 crossref_primary_10_1016_j_comcom_2020_07_025 crossref_primary_10_1007_s11276_022_03189_1 crossref_primary_10_1109_TCCN_2024_3391318 crossref_primary_10_1109_TVT_2022_3143500 crossref_primary_10_3390_photonics9030184 crossref_primary_10_3390_electronics12245036 crossref_primary_10_3390_telecom4040037 crossref_primary_10_3390_electronics11010065 crossref_primary_10_1049_tje2_12156 crossref_primary_10_1007_s11468_024_02291_8 crossref_primary_10_1109_TVT_2024_3371029 crossref_primary_10_3390_electronics12244959 crossref_primary_10_1109_TIV_2022_3195635 crossref_primary_10_1109_LWC_2023_3272974 crossref_primary_10_3390_electronics12143129 crossref_primary_10_1109_TWC_2024_3357071 crossref_primary_10_3390_s21062015 crossref_primary_10_1631_FITEE_2000443 crossref_primary_10_1109_TVT_2023_3337648 crossref_primary_10_1631_FITEE_2400464 crossref_primary_10_3390_electronics13152981 crossref_primary_10_1007_s11036_020_01670_9 crossref_primary_10_1016_j_comnet_2024_110697 crossref_primary_10_1109_ACCESS_2021_3054833 crossref_primary_10_1587_elex_18_20210429
Cites_doi	10.2514/3.25422 10.1109/JIOT.2018.2848295 10.1109/ETFA.2005.1612506 10.1109/VTCFall.2015.7390797 10.1109/TBDATA.2018.2840696 10.1109/JSAC.2003.810294 10.1109/TVT.2016.2585504 10.1049/el:19931092 10.1109/EuCAP.2012.6206356 10.1155/2015/372124 10.1109/infcomw.2017.8116491 10.1049/iet-map.2018.6187 10.1109/JSAC.2017.2710758 10.1109/TVT.2018.2851783 10.1109/MAP.2014.7011023 10.1109/TVT.2016.2530306 10.1109/TVT.2018.2878352 10.1007/s11432-016-9144-x 10.1007/978-3-540-28650-9_4 10.1155/2013/378407 10.1109/WCNC.2016.7564890 10.1109/PIMRC.2018.8580938 10.1016/j.dsp.2016.08.014 10.1109/TVT.2016.2563038 10.1115/1.3662552 10.1109/WCNC.2009.4917538 10.23919/EuCAP.2017.7928124 10.1109/TMTT.2011.2178859 10.1109/CC.2016.7833457 10.1109/COMST.2018.2862141 10.1631/FITEE.1601817 10.1109/WCNC.2018.8377337 10.1109/glocomw.2018.8644245 10.1109/JIOT.2018.2874816 10.1109/EuCAP.2014.6902475 10.1109/VETEC.1996.501466 10.1109/GLOCOM.2014.7037248 10.1109/DASC.2014.6979495 10.1109/ACCESS.2017.2652983 10.1109/RWS.2011.5725435 10.1109/25.289418 10.1109/ACCESS.2018.2793298 10.1109/MILCOM.2005.1606122 10.1109/JSTSP.2017.2788405 10.1109/TVT.2016.2542106 10.1049/el:20052444 10.1109/SICON.2005.257875 10.1109/TWC.2008.070143 10.1109/EuCAP.2016.7481470 10.1109/MWC.001.1900323 10.1162/neco.1997.9.8.1735 10.1109/25.845094 10.1109/JSYST.2015.2477503 10.1214/aoms/1177699147 10.1109/IMCCC.2016.123 10.1049/el:19870712 10.1109/8.1081 10.1109/JSAC.2017.2679660 10.1109/MCOM.2014.6979985 10.1109/COMST.2019.2915069 10.1109/T-VT.1980.23854 10.1109/COMST.2018.2841996 10.1109/ICUMT.2017.8255203 10.1109/4234.922757 10.1109/MILCOM.2003.1290436 10.1109/MCOM.2018.1700846 10.1049/cp.2018.0453 10.23919/ICACT.2018.8323708 10.1109/MWC.2016.1500356WC 10.1109/TAP.1987.1144137 10.1109/TAP.2011.2122294 10.1109/25.994803 10.1631/FITEE.1700021 10.1109/TWC.2007.051050 10.1109/PIMRC.2014.7136161 10.1049/iet-map.2017.0711 10.1049/iet-com.2012.0028 10.1109/MCOM.2014.6829967 10.1109/GLOCOM.2016.7842372 10.1109/JCN.2013.000103 10.1109/TAP.1986.1143781 10.1007/s41650-017-0004-z 10.1002/2013RS005292 10.1109/PIMRC.2018.8580992 10.1109/ICC.2018.8422221 10.1109/GLOCOMW.2011.6162389 10.1109/TVT.2015.2419738 10.1109/WiCOM.2012.6478340 10.1109/TVT.2017.2659651 10.1109/TWC.2013.072313.121581 10.1109/TAP.2008.922651 10.1109/GLOCOMW.2015.7414180 10.1109/VTCFall.2016.7881093 10.1109/TMC.2017.2742949 10.1364/OL.20.001716 10.1109/JSTQE.2007.910984 10.1109/GLOCOMW.2014.7063445 10.1109/LWC.2015.2417559 10.1155/2018/9783863 10.1109/DASC.2011.6095912 10.1109/TAP.2017.2734243 10.1109/TVT.2014.2358191 10.1109/VETECF.2009.5379031 10.1109/ICC.2016.7511280 10.1109/VETECS.2006.1683399 10.1109/TTHZ.2011.2153610 10.1109/TWC.2010.092810.091092
ClassificationCodes	TN929.5
ContentType	Journal Article
Copyright	Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020. Copyright © Wanfang Data Co. Ltd. All Rights Reserved.
Copyright_xml	– notice: Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 – notice: Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020. – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved.
DBID	AAYXX CITATION 8FE 8FG ABJCF AFKRA ARAPS AZQEC BENPR BGLVJ CCPQU DWQXO GNUQQ HCIFZ JQ2 K7- L6V M7S P5Z P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PTHSS 2B. 4A8 92I 93N PSX TCJ
DOI	10.1631/FITEE.1900450
DatabaseName	CrossRef ProQuest SciTech Collection ProQuest Technology Collection ProQuest Materials Science & Engineering ProQuest Central Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Central Technology collection ProQuest One Community College ProQuest Central Korea ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database ProQuest Engineering Collection Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ)
DatabaseTitle	CrossRef Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Engineering Collection ProQuest Central Korea ProQuest Central (New) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition Materials Science & Engineering Collection ProQuest One Academic ProQuest One Academic (New)
DatabaseTitleList	Computer Science Database
Database_xml	– sequence: 1 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Computer Science
EISSN	2095-9230
EndPage	61
ExternalDocumentID	zjdxxbc_e202001005 10_1631_FITEE_1900450
GrantInformation_xml	– fundername: the National Key R&D Program of China; the National Science Fund for Distinguished Young Scholars, China; the Key Project of State Key Lab of Networking and Switching Technology, China; Huawei, and ZTE Corporation funderid: (2018YFB1801101); (61925102); (NST20180105); Huawei, and ZTE Corporation
GroupedDBID	-EM -SI -S~ 0R~ 2KG 4.4 406 5VR 96X AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAXDM AAYIU AAYTO AAYZH AAZMS ABAKF ABDZT ABECU ABFTD ABFTV ABJCF ABJNI ABJOX ABKCH ABMQK ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACIWK ACKNC ACMDZ ACMLO ACOKC ACPIV ACZOJ ADINQ ADKNI ADKPE ADRFC ADURQ ADYFF ADZKW AEBTG AEFQL AEGNC AEJHL AEJRE AEMSY AENEX AEOHA AESKC AETCA AEVLU AEXYK AFBBN AFKRA AFLOW AFQWF AFUIB AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AILAN AITGF AJBLW AJRNO AJZVZ ALFXC ALMA_UNASSIGNED_HOLDINGS AMKLP AMXSW AMYLF ANMIH AOCGG ARAPS AXYYD BENPR BGLVJ BGNMA CAJEI CCEZO CCPQU CHBEP CUBFJ CW9 DDRTE DNIVK DPUIP EBLON EBS EIOEI EJD FA0 FERAY FIGPU FINBP FNLPD FRRFC FSGXE FYJPI GGCAI GGRSB HCIFZ IKXTQ IWAJR J-C JUIAU JZLTJ K7- KOV LLZTM M4Y M7S NPVJJ NQJWS NU0 O9J PT4 PTHSS Q-- R-I RLLFE ROL RSV S.. SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE TCJ TGT TSG U1G U5S UG4 UOJIU UTJUX UZXMN VFIZW Z7R Z7X Z7Z Z83 Z88 ZMTXR AAPKM AAYXX ABBRH ABDBE ABFSG ACSTC AEZWR AFDZB AFHIU AFOHR AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT 8FE 8FG ABRTQ AZQEC DWQXO GNUQQ JQ2 L6V P62 PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PUEGO 2B. 4A8 92I 93N PMFND PSX
ID	FETCH-LOGICAL-c339t-d911dd40ad9b51ed85689fd34e72180f61925cc99e3780bd24aaa58f81fd4de23
IEDL.DBID	AGYKE
ISSN	2095-9184
IngestDate	Thu May 29 04:06:16 EDT 2025 Wed Sep 24 02:49:48 EDT 2025 Thu Apr 24 23:11:41 EDT 2025 Tue Jul 01 03:03:18 EDT 2025 Fri Feb 21 02:35:18 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Machine learning Channel measurements Sixth generation Terahertz Channel models TN929.5 Space-air-ground integrated network Industrial Internet of Things
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c339t-d911dd40ad9b51ed85689fd34e72180f61925cc99e3780bd24aaa58f81fd4de23
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-6492-3846 0000-0003-0432-7361
PQID	2918726261
PQPubID	2044401
PageCount	23
ParticipantIDs	wanfang_journals_zjdxxbc_e202001005 proquest_journals_2918726261 crossref_citationtrail_10_1631_FITEE_1900450 crossref_primary_10_1631_FITEE_1900450 springer_journals_10_1631_FITEE_1900450
ProviderPackageCode	CITATION AAYXX
PublicationCentury	2000
PublicationDate	20200100 2020-01-00 20200101 2020
PublicationDateYYYYMMDD	2020-01-01
PublicationDate_xml	– month: 1 year: 2020 text: 20200100
PublicationDecade	2020
PublicationPlace	Hangzhou
PublicationPlace_xml	– name: Hangzhou – name: Heidelberg
PublicationTitle	Frontiers of information technology & electronic engineering
PublicationTitleAbbrev	Front Inform Technol Electron Eng
PublicationTitle_FL	Frontiers of Information Technology & Electronic Engineering
PublicationYear	2020
Publisher	Zhejiang University Press Springer Nature B.V State Key Lab of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
Publisher_xml	– name: Zhejiang University Press – name: Springer Nature B.V – name: State Key Lab of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
References	Pometcu L, D’Errico R, 2018. Large scale and clusters characteristics in indoor sub-THz channels. Proc 29th Annual Int Symp Personal Indoor and Mobile Radio Communications, p.1405–1409. https://doi.org/10.1109/PIMRC.2018.8580938 WillinkTJSquiresCCColmanGWMeasurement and characterization of low-altitude air-to-ground MIMO channelsIEEE Trans Veh Technol20156542637264810.1109/TVT.2015.2419738 Khalid N, Akan OB, 2016. Wideband THz communication channel measurements for 5G indoor wireless networks. IEEE Int Conf on Communications. https://doi.org/10.1109/ICC.2016.7511280 Richter F, Fehske AJ, Fettweis GP, 2009. Energy efficiency aspects of base station deployment strategies for cellular networks. IEEE 70th Vehicular Technology Conf, p.1–5. https://doi.org/10.1109/VETECF.2009.5379031 MatolakDWSunRYAir-ground channel characterization for unmanned aircraft systems. Part I: methods, measurements, and models for over-water settingsIEEE Trans Veh Technol2017661264410.1109/TVT.2016.2530306 PriebeSKuernerTStochastic modeling of THz indoor radio channelsIEEE Trans Wirel Commun20131294445445510.1109/TWC.2013.072313.121581 Holfeld B, Wieruch D, Raschkowski L, et al., 2016. Radio channel characterization at 5.85 GHz for wireless M2M communication of industrial robots. IEEE Wireless Communications and Networking Conf, p.1–7. https://doi.org/10.1109/WCNC.2016.7564890 Nikolaidis V, Moraitis N, Kanatas AG, 2016. Dual polarized MIMO LMS channel measurements and characterization in a pedestrian environment. 10th European Conf on Antennas and Propagation, p.1–5. https://doi.org/10.1109/EuCAP.2016.7481470 CMCC, BUPT, 2018a. New Measurements and Modelling on Fast Fading in IIOT Scenarios. Proposal RP-1904743, 3GPP. HochreiterSSchmidhuberJLong short-term memoryNeur Comput1997971735178010.1162/neco.1997.9.8.1735 Berardinelli G, Mahmood NH, Rodriguez I, et al., 2018. Beyond 5G wireless IRT for Industry 4.0: design principles and spectrum aspects. IEEE Globecom Workshops, p.1–6. https://doi.org/10.1109/glocomw.2018.8644245 PiesiewiczRJacobMKochMPerformance analysis of future multigigabit wireless communication systems at THz frequencies with highly directive antennas in realistic indoor environmentsIEEE J Sel Top Quant Electron200814242143010.1109/JSTQE.2007.910984 LiuGYHouXYWangFAchieving 3D-MIMO with massive antennas from theory to practice with evaluation and field trial resultsIEEE Syst J2016111627110.1109/JSYST.2015.2477503 DahlmanEMildhGParkvallS5G wireless access: requirements and realizationIEEE Commun Mag20145212424710.1109/MCOM.2014.6979985 LuBWangCXJieHPredicting wireless mmwave massive MIMO channel characteristics using machine learning algorithmsWirel Commun Mob Comput201820189783863 Ferrer-CollJÄngskogPChiloJCharacterisation of highly absorbent and highly reflective radio wave propagation environments in industrial applicationsIET Commun20126152404241210.1049/iet-com.2012.0028 Li YP, Zhang JH, Ma ZY, et al., 2018. Clustering analysis in the wireless propagation channel with a variational Gaussian mixture model. IEEE Trans Big Data, online. https://doi.org/10.1109/TBDATA.2018.2840696 JansenCPiesiewiczRMittlemanDThe impact of reflections from stratified building materials on the wave propagation in future indoor terahertz communication systemsIEEE Trans Antenn Propag20085651413141910.1109/TAP.2008.922651 Rey S, Eckhardt JM, Peng B, et al., 2017. Channel sounding techniques for applications in THz communications: a first correlation based channel sounder for ultrawideband dynamic channel measurements at 300 GHz. Proc 9th Int Con gress on Ultra Modern Telecommunications and Control Systems and Workshops, p.449–453. https://doi.org/10.1109/ICUMT.2017.8255203 LuanFYZhangYXiaoLMFading characteristics of wireless channel on high-speed railway in hilly terrain scenarioInt J Antenn Propag2013201337840710.1155/2013/378407 QuinlanJRInduction of decision treesMach Learn19861181106 Navabi S, Wang CW, Bursalioglu OY, et al., 2018. Predicting wireless channel features using neural networks. IEEE Int Conf on Communications, p.1–6. https://doi.org/10.1109/ICC.2018.8422221 RiecheMIhlowAArndtDModeling of the land mobile satellite channel considering the terminal’s driving directionInt J Antenn Propag2015201537212410.1155/2015/372124 CerwallPJonssonPMöllerREricsson Mobility Report2015Stockholm, SwedenTelefonaktiebolaget LM Ericsson LiuJJShiYPFadlullahZMSpace-air-ground integrated network: a surveyIEEE Commun Surv Tutor20182042714274110.1109/COMST.2018.2841996 ChengXLiYRA 3-D geometry-based stochastic model for UAV-MIMO wideband nonstationary channelsIEEE Int Things J2019621654166210.1109/JIOT.2018.2874816 GoldhirshJVogelWRoadside tree attenuation measurements at UHF for land mobile satellite systemsIEEE Trans Antenn Propag198735558959610.1109/TAP.1987.1144137 WangCXBianJSunJA survey of 5G channel measurements and modelsIEEE Commun Surv Tutor20182043142316810.1109/COMST.2018.2862141 Zhang C, Hui YN, 2011. Broadband air-to-ground communications with adaptive MIMO datalinks. IEEE/AIAA 30th Digital Avionics Systems Conf, p.4D4-1. https://doi.org/10.1109/DASC.2011.6095912 PriebeSJastrowCJacobMChannel and propagation measurements at 300 GHzIEEE Trans Antenn Propag20115951688169810.1109/TAP.2011.2122294 Arndt D, Ihlow A, Heuberger A, et al., 2011. Antenna diversity for mobile satellite applications: performance evaluation based on measurements. Proc 5th European Conf on Antennas and Propagation, p.3729–3733. HaasEAeronautical channel modelingIEEE Trans Veh Technol2002512254264162075710.1109/25.994803 3GPP, 2019. Study on Evaluation Methodology of New Vehicle-to-Everything (V2X) Use Cases for LTE and NR. Technical Report TR 37.885, 3GPP. Ai Y, Cheffena M, Li Q, 2015. Radio frequency measurements and capacity analysis for industrial indoor environments. Proc 9th European Conf on Antennas and Propagation, p.1–5. WangZYShenCSmall cell transmit power assignment based on correlated bandit learningIEEE J Sel Area Commun20173551030104510.1109/JSAC.2017.2679660 WangZLiLXuYHandover control in wireless systems via asynchronous multiuser deep reinforcement learningIEEE Int Thing J2018564296430710.1109/JIOT.2018.2848295 Dai L, Zhang H, Zhuang Y, 2018. Propagation-model-free coverage evaluation via machine learning for future 5G networks. IEEE 29th Annual Int Symp on Personal, Indoor and Mobile Radio Communications, p.1–5. https://doi.org/10.1109/PIMRC.2018.8580992 Martínez ÀO, de Carvalho E, Nielsen JØ, 2014. Towards very large aperture massive MIMO: a measurement based study. IEEE Globecom Workshops, p.281–286. https://doi.org/10.1109/GLOCOMW.2014.7063445 ZhangPNiuKTianHThe outlook for 6G mobile communication technologiesJ Commun201941145152 LiHHLiYZZhouSDWireless channel feature extraction via GMM and CNN in the tomographic channel modelJ Commun Inform Netw201721415110.1007/s41650-017-0004-z Chen XB, Tian L, Tang P, et al., 2016. Modelling of human body shadowing based on 28 GHz indoor measurement results. IEEE 84th Vehicular Technology Conf, p.1–5. https://doi.org/10.1109/VTCFall.2016.7881093 ZhangJPanCPeiFThree-dimensional fading channel models: a survey of elevation angle researchIEEE Commun Mag201452621822610.1109/MCOM.2014.6829967 JiangCXZhangHJRenYMachine learning paradigms for next-generation wireless networksIEEE Wirel Commun20162429810510.1109/MWC.2016.1500356WC Liu L, Zhang K, Tao C, et al., 2018. Channel measurements and characterizations for automobile factory environments. 20th Int Conf on Advanced Communication Technology, p.234–238. https://doi.org/10.23919/ICACT.2018.8323708 KhawajaWGuvencIMatolakDWA survey of air-to-ground propagation channel modeling for unmanned aerial vehiclesIEEE Commun Surv Tutor20192132361239110.1109/COMST.2019.2915069 VogelWJGoldhirshJTree attenuation at 869 MHz derived from remotely piloted aircraft measurementsIEEE Trans Antenn Propag198634121460146410.1109/TAP.1986.1143781 JacobMPriebeSDickhoffRDiffraction in mm and sub-mm wave indoor propagation channelsIEEE Trans Microw Theory Technol201260383384410.1109/TMTT.2011.2178859 LutzECyganDDippoldMThe land mobile satellite communication channel-recording, statistics, and channel modelIEEE Trans Veh Technol199140237538610.1109/25.289418 Strinati EC, Barbarossa S, Gonzalez-Jimenez JL, et al., 2019. 6G: the next frontier. https://arxiv.org/abs/1901.03239 Ono F, Takizawa K, Tsuji H, et al., 2015. S-band radio propagation characteristics in urban environment for unmanned aircraft systems. Int Symp on Antennas and Propagation, p.1–4. Ericsson, 2019b. Views on Additional Modelling Components. Proposal RP-1905203, 3GPP. Matolak DW, Sen I, Xiong WH, et al., 2005. 5 GHz wireless channel characterization for vehicle to vehicle communications. IEEE Military Communications Conf, p.3016–3022. https://doi.org/10.1109/MILCOM.2005.1606122 LiWZLawCLDubeyVKKa-band land mobile satellite channel model incorporating weather effectsIEEE Commun Lett20015519419610.1109/4234.922757 Luo SP, Polu N, Chen ZX, et al., 2011. RF channel modeling of a WSN testbed for industrial environment. IEEE Radio and Wireless Symp, p.375–378. https://doi.org/10.1109/RWS.2011.5725435 Miaoudakis A, Lekkas A, Kalivas G, et al., 2005. Radio channel characterization in industrial environments and spread spectrum modem performance. IEEE Conf on Emerging Technologies and Factory Automation, p.87–93. https://doi.org/10.1109/ETFA.2005.1612506 LinLZhuMEfficient tracking of moving target based on an improved fast differential evolution algorithmIEEE Access201866820682810.1109/ACCESS.2018.2793298 HuangHJYangJSongYDeep learning for super-resolution channel estimation and DOA estimation based massive MIMO systemIEEE Trans Veh Technol20186798549856010.1109/TVT.2018.2851783 MatolakDWSunRYAir-ground channel characterization for unmanned aircraft systems. Part III: the suburban and near-urban environmentsIEEE Trans Veh Technol20176686607661810.1109/TVT.2017.2659651 WP5D IGuidelines for Evaluation of Radio Interface Technologies for IMT-20202017Geneva, SwitzerlandITU-R DreyfusSEArtificial neural WZ Li (1480_CR67) 2001; 5 1480_CR34 1480_CR35 HJ Huang (1480_CR45) 2018; 67 1480_CR30 1480_CR112 R Piesiewicz (1480_CR101) 2008; 14 1480_CR39 S Priebe (1480_CR105) 2013; 15 J Karedal (1480_CR56) 2007; 6 B Lu (1480_CR76) 2018; 2018 1480_CR102 WP5D I (1480_CR135) 2017 TS Rappaport (1480_CR109) 1987; 23 L Lin (1480_CR70) 2018; 6 JZ Li (1480_CR65) 2017; 18 Y Freund (1480_CR32) 1999; 14 S Hochreiter (1480_CR41) 1997; 9 1480_CR25 PD Moral (1480_CR91) 1996; 2 1480_CR21 GS Yang (1480_CR137) 2019; 13 1480_CR22 1480_CR20 1480_CR120 1480_CR121 C Jansen (1480_CR51) 2008; 56 1480_CR29 SJ Darak (1480_CR26) 2017; 60 J Goldhirsh (1480_CR36) 1987; 35 CX Jiang (1480_CR53) 2016; 24 1480_CR28 M Jacob (1480_CR50) 2012; 60 1480_CR117 1480_CR118 CE Rasmussen (1480_CR111) 2003 JJ Chen (1480_CR14) 2017; 5 1480_CR113 SE Dreyfus (1480_CR27) 2012; 13 C Cortes (1480_CR23) 1995; 20 W Li (1480_CR66) 2019; 16 JR Quinlan (1480_CR107) 1986; 1 S Priebe (1480_CR106) 2014; 49 1480_CR15 1480_CR98 1480_CR11 MK Samimi (1480_CR115) 2015; 4 1480_CR96 1480_CR97 Z Wang (1480_CR130) 2018; 5 E Nachmani (1480_CR93) 2018; 12 E Dahlman (1480_CR24) 2014; 52 E Ali (1480_CR5) 2017; 18 BB Hu (1480_CR43) 1995; 20 CX Wang (1480_CR129) 2018; 20 LE Baum (1480_CR10) 1966; 37 1480_CR17 DW Matolak (1480_CR85) 2017; 66 S Kim (1480_CR60) 2015; 64 1480_CR94 ITU-R (1480_CR47) 2013 1480_CR95 TS Rappaport (1480_CR110) 2017; 65 1480_CR92 E Tanghe (1480_CR124) 2008; 7 1480_CR89 1480_CR87 1480_CR88 R Piesiewicz (1480_CR100) 2005; 41 Cisco (1480_CR19) 2019 JJ Liu (1480_CR72) 2018; 20 J Zhang (1480_CR141) 2014; 52 JH Zhang (1480_CR143) 2017; 35 J Zhang (1480_CR140) 2016; 13 TJ Willink (1480_CR134) 2015; 65 ITU-R (1480_CR48) 2015 RY Sun (1480_CR122) 2017; 66 XF Chen (1480_CR16) 2018; 17 E Lutz (1480_CR79) 1991; 40 XQ Liu (1480_CR74) 2017; 66 EM Joo (1480_CR54) 2009 1480_CR83 1480_CR84 W Khawaja (1480_CR59) 2019; 21 1480_CR81 1480_CR80 C Jansen (1480_CR52) 2011; 1 FY Luan (1480_CR77) 2013; 2013 1480_CR2 1480_CR78 1480_CR1 WJ Vogel (1480_CR127) 1988; 36 X Gao (1480_CR33) 2013; 10 1480_CR75 GY Liu (1480_CR71) 2016; 11 DW Matolak (1480_CR86) 2017; 66 M Series (1480_CR116) 2015 J Ferrer-Coll (1480_CR31) 2012; 6 YJ Xie (1480_CR136) 2000; 49 1480_CR73 GC Hess (1480_CR40) 1980; 29 X Cheng (1480_CR18) 2019; 6 1480_CR69 A Goldsmith (1480_CR37) 2003; 21 1480_CR68 TL Marzetta (1480_CR82) 2010; 9 1480_CR63 HH Li (1480_CR64) 2017; 2 P Zhang (1480_CR145) 2019; 4 1480_CR61 1480_CR62 RE Kalman (1480_CR55) 1960; 82 P Tang (1480_CR123) 2018; 68 JH Zhang (1480_CR142) 2017; 60 1480_CR58 CM Bishop (1480_CR12) 2006 AM Al-Saegh (1480_CR8) 2017; 66 1480_CR57 C Watkins (1480_CR132) 1989 WJ Vogel (1480_CR126) 1986; 34 1480_CR133 P Petropoulou (1480_CR99) 2014; 56 S Priebe (1480_CR103) 2013; 12 P Cerwall (1480_CR13) 2015 1480_CR125 M Simunek (1480_CR119) 2011; 20 ZY Wang (1480_CR131) 2017; 35 M Rieche (1480_CR114) 2015; 2015 S Priebe (1480_CR104) 2011; 59 1480_CR46 ITU-T (1480_CR49) 2019 1480_CR44 1480_CR42 WJ Vogel (1480_CR128) 1993; 29 E Haas (1480_CR38) 2002; 51 AF Molisch (1480_CR90) 2012 1480_CR139 1480_CR138 1480_CR7 1480_CR9 1480_CR4 X Raimundo (1480_CR108) 2018; 12 1480_CR3 1480_CR6 JH Zhang (1480_CR144) 2018; 56
References_xml	– reference: CerwallPJonssonPMöllerREricsson Mobility Report2015Stockholm, SwedenTelefonaktiebolaget LM Ericsson – reference: TangPZhangJMolischAFEstimation of the K-factor for temporal fading from single-snapshot wideband measurementsIEEE Trans Veh Technol2018681496310.1109/TVT.2018.2878352 – reference: Berardinelli G, Mahmood NH, Rodriguez I, et al., 2018. Beyond 5G wireless IRT for Industry 4.0: design principles and spectrum aspects. IEEE Globecom Workshops, p.1–6. https://doi.org/10.1109/glocomw.2018.8644245 – reference: AliEIsmailMNordinRBeamforming techniques for massive MIMO systems in 5G: overview, classification, and trends for future researchFront Inform Technol Electron Eng201718675377210.1631/FITEE.1601817 – reference: WatkinsCLearning from Delayed Rewards1989Cambridge, UKUniversity of Cambridge – reference: Chen XB, Tian L, Tang P, et al., 2016. Modelling of human body shadowing based on 28 GHz indoor measurement results. IEEE 84th Vehicular Technology Conf, p.1–5. https://doi.org/10.1109/VTCFall.2016.7881093 – reference: Ono F, Takizawa K, Tsuji H, et al., 2015. S-band radio propagation characteristics in urban environment for unmanned aircraft systems. Int Symp on Antennas and Propagation, p.1–4. – reference: WangCXBianJSunJA survey of 5G channel measurements and modelsIEEE Commun Surv Tutor20182043142316810.1109/COMST.2018.2862141 – reference: Strinati EC, Barbarossa S, Gonzalez-Jimenez JL, et al., 2019. 6G: the next frontier. https://arxiv.org/abs/1901.03239 – reference: Lei MY, Zhang JH, Lei T, et al., 2015. 28-GHz indoor channel measurements and analysis of propagation characteristics. IEEE 25th Annual Int SymponPersonal, Indoor, and Mobile Radio Communication. https://doi.org/10.1109/PIMRC.2014.7136161 – reference: XieYJFangYGA general statistical channel model for mobile satellite systemsIEEE Trans Veh Technol200049374475210.1109/25.845094 – reference: SunRYMatolakDWAir-ground channel characterization for unmanned aircraft systems. Part II: hilly and mountainous settingsIEEE Trans Veh Technol20176631913192510.1109/TVT.2016.2585504 – reference: CiscoCisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2017–2022 White Paper2019CA, USACisco Systems, Inc. – reference: QuinlanJRInduction of decision treesMach Learn19861181106 – reference: Solomitckii D, Orsino A, Andreev S, et al., 2018. Characterization of mmWave channel properties at 28 and 60 GHz in factory automation deployments. IEEE Wireless Communications and Networking Conf, p.1–6. https://doi.org/10.1109/WCNC.2018.8377337 – reference: LutzECyganDDippoldMThe land mobile satellite communication channel-recording, statistics, and channel modelIEEE Trans Veh Technol199140237538610.1109/25.289418 – reference: DarakSJZhangHGPalicotJDecision making policy for RF energy harvesting enabled cognitive radios in decentralized wireless networksDig Signal Process201760334510.1016/j.dsp.2016.08.014 – reference: LiuJJShiYPFadlullahZMSpace-air-ground integrated network: a surveyIEEE Commun Surv Tutor20182042714274110.1109/COMST.2018.2841996 – reference: Almeida JJH, Lopes PB, Akamine C, et al., 2018. An application of neural networks to channel estimation of the ISDB-TB FBMC system. https://arxiv.org/abs/1803.01141 – reference: CMCC, BUPT, 2018b. New Measurements and Modelling on Pathloss in IIOT Scenarios. Proposal RP-1904742, 3GPP. – reference: PiesiewiczRKleine-OstmannTKrumbholzNTerahertz characterisation of building materialsElectron Lett200541181002100410.1049/el:20052444 – reference: Sexton D, Mahony M, Lapinski M, et al., 2005. Radio channel quality in industrial wireless sensor networks. Sensors for Industry Conf, p.88–94. https://doi.org/10.1109/SICON.2005.257875 – reference: Yanmaz E, Kuschnig R, Bettstetter C, 2011. Channel measurements over 802.11a-based UAV-to-ground links. IEEE GLOBECOM Workshops, p.1280–1284. https://doi.org/10.1109/GLOCOMW.2011.6162389 – reference: MolischAFWireless Communications2012New YorkJohn Wiley & Sons – reference: RappaportTSMcGillemCDCharacterising the UHF factory radio channelElectron Lett198723191015101710.1049/el:19870712 – reference: MarzettaTLNoncooperative cellular wireless with unlimited numbers of base station antennasIEEE Trans Wirel Commun20109113590360010.1109/TWC.2010.092810.091092 – reference: Khawaja W, Guvenc I, Matolak D, 2016. UWB channel sounding and modeling for UAV air-to-ground propagation channels. IEEE Global Communications Conf, p.1–7. https://doi.org/10.1109/GLOCOM.2016.7842372 – reference: LinLZhuMEfficient tracking of moving target based on an improved fast differential evolution algorithmIEEE Access201866820682810.1109/ACCESS.2018.2793298 – reference: WangZYShenCSmall cell transmit power assignment based on correlated bandit learningIEEE J Sel Area Commun20173551030104510.1109/JSAC.2017.2679660 – reference: MatolakDWSunRYAir-ground channel characterization for unmanned aircraft systems. Part I: methods, measurements, and models for over-water settingsIEEE Trans Veh Technol2017661264410.1109/TVT.2016.2530306 – reference: CMRI, 2019. The Outlook and Demand Report for 2030+. China Mobile Resesrch Institute, Bejing (in Chinese). https://cmri.chinamobile.com/news/5985.html [Accessed on Jan. 4, 2020]. – reference: KaredalJWyneSAlmersPA measurement-based statistical model for industrial ultra-wideband channelsIEEE Trans Wirel Commun2007683028303710.1109/TWC.2007.051050 – reference: PriebeSKuernerTStochastic modeling of THz indoor radio channelsIEEE Trans Wirel Commun20131294445445510.1109/TWC.2013.072313.121581 – reference: Goddemeier N, Wietfeld C, 2015. Investigation of air-to-air channel characteristics and a UAV specific extension to the rice model. IEEE Globecom Workshops, p.1–5. https://doi.org/10.1109/GLOCOMW.2015.7414180 – reference: Li Y, Zhao L, Wang H, 2012. A novel mobility model for clustered MANET. 8th Int Conf on Wireless Communications, Networking and Mobile Computing, p.1–4. https://doi.org/10.1109/WiCOM.2012.6478340 – reference: Newhall WG, Mostafa R, Dietrich C, et al., 2003. Wideband air-to-ground radio channel measurements using an antenna array at 2 GHz for low-altitude operations. IEEE Military Communications Conf, p.1422–1427. https://doi.org/10.1109/MILCOM.2003.1290436 – reference: Lacoste F, Lemorton J, Casadebaig L, et al., 2012. Measurements of the land mobile and nomadic satellite channels at 2.2 GHz and 3.8 GHz. 6th European Conf on Antennas and Propagation, p.2422–2426. https://doi.org/10.1109/EuCAP.2012.6206356 – reference: VogelWJGoldhirshJFade measurements at L-band and UHF in mountainous terrain for land mobile satellite systemsIEEE Trans Antenn Propag198836110411310.1109/8.1081 – reference: LiWZhangJHMaXCThe way to apply machine learning to IoT driven wireless network from channel perspectiveChina Commun2019161148164 – reference: Pometcu L, D’Errico R, 2018. Large scale and clusters characteristics in indoor sub-THz channels. Proc 29th Annual Int Symp Personal Indoor and Mobile Radio Communications, p.1405–1409. https://doi.org/10.1109/PIMRC.2018.8580938 – reference: Zhang C, Hui YN, 2011. Broadband air-to-ground communications with adaptive MIMO datalinks. IEEE/AIAA 30th Digital Avionics Systems Conf, p.4D4-1. https://doi.org/10.1109/DASC.2011.6095912 – reference: HessGCLand-mobile satellite excess path loss measurementsIEEE Trans Veh Technol198029229029710.1109/T-VT.1980.23854 – reference: RaimundoXSalousSCheemaAIndoor dual polarised radio channel characterisation in the 54 and 70 GHz bandsIET Microw Antenn Propag20181281287129210.1049/iet-map.2017.0711 – reference: Ferrer-CollJÄngskogPChiloJCharacterisation of highly absorbent and highly reflective radio wave propagation environments in industrial applicationsIET Commun20126152404241210.1049/iet-com.2012.0028 – reference: 3GPP, 2018. Study on Channel Model for Frequencies from 0.5 to 100 GHz. Technical Report TR 38.901, 3GPP. – reference: Miaoudakis A, Lekkas A, Kalivas G, et al., 2005. Radio channel characterization in industrial environments and spread spectrum modem performance. IEEE Conf on Emerging Technologies and Factory Automation, p.87–93. https://doi.org/10.1109/ETFA.2005.1612506 – reference: SimunekMPechacPFontanFPExcess loss model for low elevation links in urban areas for UAVsRadioengineering2011203561568 – reference: GaoXChenZHuYAnalysis ofunmanned aerial vehicle MIMO channel capacity based on aircraft attitudeWSEAS Trans Inform Sci Appl20131025867 – reference: Wentz M, Stojanovic M, 2015. A MIMO radio channel model for low-altitude air-to-ground communication systems. IEEE 82nd Vehicular Technology Conf, p.1–6. https://doi.org/10.1109/VTCFall.2015.7390797 – reference: KalmanREA new approach to linear filtering and prediction problemsJ Bas Eng19608213545393199310.1115/1.3662552 – reference: RiecheMIhlowAArndtDModeling of the land mobile satellite channel considering the terminal’s driving directionInt J Antenn Propag2015201537212410.1155/2015/372124 – reference: TangheEJosephWVerloockLThe industrial indoor channel: large-scale and temporal fading at 900, 2400, and 5200 MHzIEEE Trans Wirel Commun2008772740275110.1109/TWC.2008.070143 – reference: PriebeSKannichtMJacobMUltra broadband indoor channel measurements and calibrated ray tracing propagation modeling at THz frequenciesJ Commun Netw201315654755810.1109/JCN.2013.000103 – reference: Ericsson, 2019a. Summary of e]Discussion on Additional Modelling Components. Proposal RP-1905197, 3GPP. – reference: Giordani M, Polese M, Mezzavilla M, et al., 2019. Towards 6G networks: use cases and technologies. https://arxiv.org/abs/1903.12216 – reference: Alpaydin E, 2006. Introduction to Machine Learning. MIT Press, USA. Al-Hourani A, Kandeepan S, Jamalipour A, 2014. Modeling air-to-ground path loss for low altitude platforms in urban environments. IEEE Global Communications Conf, p.2898–2904. https://doi.org/10.1109/GLOCOM.2014.7037248 – reference: Holfeld B, Wieruch D, Raschkowski L, et al., 2016. Radio channel characterization at 5.85 GHz for wireless M2M communication of industrial robots. IEEE Wireless Communications and Networking Conf, p.1–7. https://doi.org/10.1109/WCNC.2016.7564890 – reference: 3GPP, 2019. Study on Evaluation Methodology of New Vehicle-to-Everything (V2X) Use Cases for LTE and NR. Technical Report TR 37.885, 3GPP. – reference: MatolakDWSunRYAir-ground channel characterization for unmanned aircraft systems. Part III: the suburban and near-urban environmentsIEEE Trans Veh Technol20176686607661810.1109/TVT.2017.2659651 – reference: PriebeSJacobMKuernerTAngular and RMS delay spread modeling in view of THz indoor communication systemsRadio Sci201449324225110.1002/2013RS005292 – reference: LiuGYHouXYWangFAchieving 3D-MIMO with massive antennas from theory to practice with evaluation and field trial resultsIEEE Syst J2016111627110.1109/JSYST.2015.2477503 – reference: LuBWangCXJieHPredicting wireless mmwave massive MIMO channel characteristics using machine learning algorithmsWirel Commun Mob Comput201820189783863 – reference: ZhangPNiuKTianHThe outlook for 6G mobile communication technologiesJ Commun201941145152 – reference: ITU-TArchitectural Framework for Machine Learning in Future Networks Including IMT-2020. Recommendation Y.31722019Geneva, SwitzerlandITU-T – reference: PetropoulouPMichailidisETPanagopoulosADRadio propagation channel measurements for multi-antenna satellite communication systems: a surveyIEEE Antenn Propag Mag201456610212210.1109/MAP.2014.7011023 – reference: GoldhirshJVogelWRoadside tree attenuation measurements at UHF for land mobile satellite systemsIEEE Trans Antenn Propag198735558959610.1109/TAP.1987.1144137 – reference: LiuXQChenHHChenSYSymbol cyclic-shift equalization algorithm—a CP-free OFDM/OFDMA system designIEEE Trans Veh Technol20176612822943597004 – reference: Nikolaidis V, Moraitis N, Kanatas AG, 2016. Dual polarized MIMO LMS channel measurements and characterization in a pedestrian environment. 10th European Conf on Antennas and Propagation, p.1–5. https://doi.org/10.1109/EuCAP.2016.7481470 – reference: Tu HD, Shimamoto S, 2009. A proposal of wide-band air-to-ground communication at airports employing 5-GHz band. IEEE Wireless Communications and Networking Conf, p.1–6. https://doi.org/10.1109/WCNC.2009.4917538 – reference: LuanFYZhangYXiaoLMFading characteristics of wireless channel on high-speed railway in hilly terrain scenarioInt J Antenn Propag2013201337840710.1155/2013/378407 – reference: 5G-ACIA, 2018. LS on Channel Model for Indoor Industrial Scenarios. Proposal RP-181521, 5G-ACIA. – reference: DreyfusSEArtificial neural networks, back propagation, and the Kelley-Bryson gradient procedureJ Guid Contr Dynam2012135926928106866910.2514/3.25422 – reference: Li YP, Zhang JH, Ma ZY, et al., 2018. Clustering analysis in the wireless propagation channel with a variational Gaussian mixture model. IEEE Trans Big Data, online. https://doi.org/10.1109/TBDATA.2018.2840696 – reference: RappaportTSXingYCMacCartneyGROverview of millimeter wave communications for fifth-generation (5G) wireless networks: with a focus on propagation modelsIEEE Trans Antenn Propag201765126213623010.1109/TAP.2017.2734243 – reference: WillinkTJSquiresCCColmanGWMeasurement and characterization of low-altitude air-to-ground MIMO channelsIEEE Trans Veh Technol20156542637264810.1109/TVT.2015.2419738 – reference: YangGSZhangYHeZWMachine-learning-based prediction methods for path loss and delay spread in air-to-ground millimetre-wave channelsIET Microw Antenn Propag20191381113112110.1049/iet-map.2018.6187 – reference: Ai Y, Cheffena M, Li Q, 2015. Radio frequency measurements and capacity analysis for industrial indoor environments. Proc 9th European Conf on Antennas and Propagation, p.1–5. – reference: BaumLEPetrieTStatistical inference for probabilistic functions of finite state Markov chainsAnn Math Stat1966376155415632022640144.4090210.1214/aoms/1177699147 – reference: SeriesMIMT Vision-Framework and Overall Objectives of the Future Development of IMT for 2020 and Beyond. Report M.2083–02015Geneva, SwitzerlandITU-R – reference: JansenCPiesiewiczRMittlemanDThe impact of reflections from stratified building materials on the wave propagation in future indoor terahertz communication systemsIEEE Trans Antenn Propag20085651413141910.1109/TAP.2008.922651 – reference: Martínez ÀO, de Carvalho E, Nielsen JØ, 2014. Towards very large aperture massive MIMO: a measurement based study. IEEE Globecom Workshops, p.281–286. https://doi.org/10.1109/GLOCOMW.2014.7063445 – reference: Lacoste F, Carvalho F, Fontan FP, et al., 2010. MISO and SIMO measurements of the land mobile satellite propagation channel at S-band. Proc 4th European Conf on Antennas and Propagation, p.1–5. – reference: Meredith J, 2016. Study on Channel Model for Frequency Spectrum above 6 GHz. Technical Report TR 38900, 3GPP. – reference: O’Shea TJ, Hoydis J, 2017. An introduction to machine learning communications systems. https://arxiv.org/abs/1702.00832v1 – reference: PiesiewiczRJacobMKochMPerformance analysis of future multigigabit wireless communication systems at THz frequencies with highly directive antennas in realistic indoor environmentsIEEE J Sel Top Quant Electron200814242143010.1109/JSTQE.2007.910984 – reference: RasmussenCEBousquetOLuxburgURätschGGaussian processes in machine learningAdvanced Lectures on Machine Learning2003Berlin HeidelbergSpringer6371 – reference: Huang C, Huang KW, Wen Y, et al., 2016. A propose of the ISS space-to-space communication system by multiplexing ground mobile communication frequency resources. 6th Int Conf on Instrumentation & Measurement, Computer, Communication and Control, p.567–569. https://doi.org/10.1109/IMCCC.2016.123 – reference: MoralPDNon-linear filtering: interacting particle resolutionMarkov Process Rel Field1996245555810879.60042 – reference: HuangHJYangJSongYDeep learning for super-resolution channel estimation and DOA estimation based massive MIMO systemIEEE Trans Veh Technol20186798549856010.1109/TVT.2018.2851783 – reference: Loo C, 1996. Statistical models for land mobile and fixed satellite communications at Ka band. Proc Vehicular Technology Conf, p.1023–1027. https://doi.org/10.1109/VETEC.1996.501466 – reference: Rey S, Eckhardt JM, Peng B, et al., 2017. Channel sounding techniques for applications in THz communications: a first correlation based channel sounder for ultrawideband dynamic channel measurements at 300 GHz. Proc 9th Int Con gress on Ultra Modern Telecommunications and Control Systems and Workshops, p.449–453. https://doi.org/10.1109/ICUMT.2017.8255203 – reference: Arndt D, Ihlow A, Heuberger A, et al., 2011. Antenna diversity for mobile satellite applications: performance evaluation based on measurements. Proc 5th European Conf on Antennas and Propagation, p.3729–3733. – reference: Shafin R, Liu LJ, Chandrasekhar V, et al., 2019. Artificial intelligence-enabled cellular networks: a critical path to beyond-5G and 6G. https://arxiv.org/abs/1907.07862 – reference: ChenJJYinXFCaiXSMeasurement-based massive MIMO channel modeling for outdoor LoS and NLoS environmentsIEEE Access201752126214010.1109/ACCESS.2017.2652983 – reference: VogelWJGoldhirshJEarth-satellite tree attenuation at 20 GHz: foliage effectsElectron Lett199329181640164110.1049/el:19931092 – reference: HochreiterSSchmidhuberJLong short-term memoryNeur Comput1997971735178010.1162/neco.1997.9.8.1735 – reference: Richter F, Fehske AJ, Fettweis GP, 2009. Energy efficiency aspects of base station deployment strategies for cellular networks. IEEE 70th Vehicular Technology Conf, p.1–5. https://doi.org/10.1109/VETECF.2009.5379031 – reference: FreundYSchapireRAbeNA short introduction to boostingJJpn Soc Artif Intell1999145771780 – reference: CortesCVapnikVSupport-vector networksMach Learn19952032732970831.68098 – reference: Ma XC, Zhang JH, Zhang YX, et al., 2017. A PCA-based modeling method for wireless MIMO channel. IEEE Conf on Computer Communications Workshops, p.874–879. https://doi.org/10.1109/infcomw.2017.8116491 – reference: Nachmani E, Marciano E, Burshtein D, et al., 2017. RNN decoding of linear block codes. https://arxiv.org/abs/1702.07560 – reference: WangZLiLXuYHandover control in wireless systems via asynchronous multiuser deep reinforcement learningIEEE Int Thing J2018564296430710.1109/JIOT.2018.2848295 – reference: ChengXLiYRA 3-D geometry-based stochastic model for UAV-MIMO wideband nonstationary channelsIEEE Int Things J2019621654166210.1109/JIOT.2018.2874816 – reference: KhawajaWGuvencIMatolakDWA survey of air-to-ground propagation channel modeling for unmanned aerial vehiclesIEEE Commun Surv Tutor20192132361239110.1109/COMST.2019.2915069 – reference: Liu L, Zhang K, Tao C, et al., 2018. Channel measurements and characterizations for automobile factory environments. 20th Int Conf on Advanced Communication Technology, p.234–238. https://doi.org/10.23919/ICACT.2018.8323708 – reference: JacobMPriebeSDickhoffRDiffraction in mm and sub-mm wave indoor propagation channelsIEEE Trans Microw Theory Technol201260383384410.1109/TMTT.2011.2178859 – reference: Matolak DW, Sun RY, 2014. Antenna and frequency diversity in the unmanned aircraft systems bands for the over-sea setting. IEEE/AIAA 33rd Digital Avionics Systems Conf, p.1–10. https://doi.org/10.1109/DASC.2014.6979495 – reference: HuBBNussMCImaging with terahertz wavesOpt Lett199520161716171810.1364/OL.20.001716 – reference: ZhangJHTangPTianL6-100 GHz research progress and challenges for fifth generation (5G) and future wireless communication from channel perspectiveSci China Inform Sci201760808030110.1007/s11432-016-9144-x – reference: SamimiMKRappaportTSMacCartneyGRProbabilistic omnidirectional path loss models for millimeter-wave outdoor communicationsIEEE Wirel Commun Lett20154435736010.1109/LWC.2015.2417559 – reference: HaasEAeronautical channel modelingIEEE Trans Veh Technol2002512254264162075710.1109/25.994803 – reference: ZhangJHZhengZZhangYX3D MIMO for 5G NR: several observations from 32 to massive 256 antennas based on channel measurementIEEE Commun Mag2018563627010.1109/MCOM.2018.1700846 – reference: PriebeSJastrowCJacobMChannel and propagation measurements at 300 GHzIEEE Trans Antenn Propag20115951688169810.1109/TAP.2011.2122294 – reference: GoldsmithAJafarSAJindalNCapacity limits of MIMO channelsIEEE J Sel Areas Commun200321568470210.1109/JSAC.2003.810294 – reference: ITU-RAttenuation by Atmospheric GasesRecommendation2013Geneva, SwitzerlandITU-R676–10 – reference: Cheng CL, Kim S, Zajić A, 2017. Comparison of path loss models for indoor 30 GHz, 140 GHz, and 300 GHz channels. Proc 11th European Conf on Antennas and Propagation, p.716–720. https://doi.org/10.23919/EuCAP.2017.7928124 – reference: LiJZAiBHeRSIndoor massive multiple-input multiple-output channel characterization and performance evaluationFront Inform Technol Electron Eng201718677378710.1631/FITEE.1700021 – reference: Matolak DW, 2015. Channel characterization for unmanned aircraft systems. 9th European Conf on Antennas and Propagation, p.1–5. – reference: ZhangJHZhangYXYuYW3D MIMO: how much does it meet our expectations observed from channel measurements?IEEE J Sel Areas Commun20173581887190310.1109/JSAC.2017.2710758 – reference: Feng QX, McGeehan J, Tameh EK, et al., 2006. Path loss models for air-to-ground radio channels in urban environments. IEEE 63rd Vehicular Technology Conf, p.2901–2905. https://doi.org/10.1109/VETECS.2006.1683399 – reference: Hanssens B, Kshetri SR, Tanghe E, et al., 2018. Measurement-based analysis of dense multipath components in a large industrial warehouse. 12th European Conf on Antennas and Propagation, p.1–5. https://doi.org/10.1049/cp.2018.0453 – reference: ZhangJThe interdisciplinary research of big data and wireless channel: a cluster-nuclei based channel modelChina Commun201613S2142610.1109/CC.2016.7833457 – reference: WP5D IGuidelines for Evaluation of Radio Interface Technologies for IMT-20202017Geneva, SwitzerlandITU-R – reference: JooEMZhouYTheory and Novel Applications of Machine Learning2009London, UKIntechOpen – reference: LiWZLawCLDubeyVKKa-band land mobile satellite channel model incorporating weather effectsIEEE Commun Lett20015519419610.1109/4234.922757 – reference: Matolak DW, Sen I, Xiong WH, et al., 2005. 5 GHz wireless channel characterization for vehicle to vehicle communications. IEEE Military Communications Conf, p.3016–3022. https://doi.org/10.1109/MILCOM.2005.1606122 – reference: Ericsson, 2019b. Views on Additional Modelling Components. Proposal RP-1905203, 3GPP. – reference: JiangCXZhangHJRenYMachine learning paradigms for next-generation wireless networksIEEE Wirel Commun20162429810510.1109/MWC.2016.1500356WC – reference: Luo SP, Polu N, Chen ZX, et al., 2011. RF channel modeling of a WSN testbed for industrial environment. IEEE Radio and Wireless Symp, p.375–378. https://doi.org/10.1109/RWS.2011.5725435 – reference: LiHHLiYZZhouSDWireless channel feature extraction via GMM and CNN in the tomographic channel modelJ Commun Inform Netw201721415110.1007/s41650-017-0004-z – reference: Navabi S, Wang CW, Bursalioglu OY, et al., 2018. Predicting wireless channel features using neural networks. IEEE Int Conf on Communications, p.1–6. https://doi.org/10.1109/ICC.2018.8422221 – reference: NachmaniEMarcianoELugoschLDeep learning methods for improved decoding of linear codesIEEE J Sel Top Signal Process201812111913110.1109/JSTSP.2017.2788405 – reference: BishopCMPattern Recognition and Machine Learning2006New YorkSpringer1107.68072 – reference: ChenXFHanZZhangHGWireless resource scheduling in virtualized radio access networks using stochastic learningIEEE Trans Mob Comput201817496197410.1109/TMC.2017.2742949 – reference: CMCC, BUPT, 2018a. New Measurements and Modelling on Fast Fading in IIOT Scenarios. Proposal RP-1904743, 3GPP. – reference: Khalid N, Akan OB, 2016. Wideband THz communication channel measurements for 5G indoor wireless networks. IEEE Int Conf on Communications. https://doi.org/10.1109/ICC.2016.7511280 – reference: ZhangJPanCPeiFThree-dimensional fading channel models: a survey of elevation angle researchIEEE Commun Mag201452621822610.1109/MCOM.2014.6829967 – reference: Al-SaeghAMSaliAMandeepJSChannel measurements, characterization, and modeling for land mobile satellite terminals in tropical regions at KubandIEEE Trans Veh Technol201766289791110.1109/TVT.2016.2563038 – reference: ITU-RIMT Traffic Estimates for the Years 2020 to 20302015Geneva, SwitzerlandITU-R – reference: DahlmanEMildhGParkvallS5G wireless access: requirements and realizationIEEE Commun Mag20145212424710.1109/MCOM.2014.6979985 – reference: Dai L, Zhang H, Zhuang Y, 2018. Propagation-model-free coverage evaluation via machine learning for future 5G networks. IEEE 29th Annual Int Symp on Personal, Indoor and Mobile Radio Communications, p.1–5. https://doi.org/10.1109/PIMRC.2018.8580992 – reference: Huawei, HiSilicon, 2018. Preliminary Channel Measurement on Large-Scale Propagation Loss for Indoor Factory Environment. Proposal RP-1904706, 3GPP. – reference: JansenCPriebeSMollerCDiffuse scattering from rough surfaces in THz communication channelsIEEE Trans Terahertz Sci Technol20111246247210.1109/TTHZ.2011.2153610 – reference: VogelWJGoldhirshJTree attenuation at 869 MHz derived from remotely piloted aircraft measurementsIEEE Trans Antenn Propag198634121460146410.1109/TAP.1986.1143781 – reference: KimSZajićAGStatistical characterization of 300-GHz propagation on a desktopIEEE Trans Veh Technol20156483330333810.1109/TVT.2014.2358191 – volume: 13 start-page: 926 issue: 5 year: 2012 ident: 1480_CR27 publication-title: J Guid Contr Dynam doi: 10.2514/3.25422 – volume: 5 start-page: 4296 issue: 6 year: 2018 ident: 1480_CR130 publication-title: IEEE Int Thing J doi: 10.1109/JIOT.2018.2848295 – ident: 1480_CR28 – volume: 14 start-page: 771 issue: 5 year: 1999 ident: 1480_CR32 publication-title: JJpn Soc Artif Intell – ident: 1480_CR2 – ident: 1480_CR34 – ident: 1480_CR89 doi: 10.1109/ETFA.2005.1612506 – volume: 10 start-page: 58 issue: 2 year: 2013 ident: 1480_CR33 publication-title: WSEAS Trans Inform Sci Appl – ident: 1480_CR121 – ident: 1480_CR133 doi: 10.1109/VTCFall.2015.7390797 – ident: 1480_CR69 doi: 10.1109/TBDATA.2018.2840696 – volume: 21 start-page: 684 issue: 5 year: 2003 ident: 1480_CR37 publication-title: IEEE J Sel Areas Commun doi: 10.1109/JSAC.2003.810294 – volume: 66 start-page: 1913 issue: 3 year: 2017 ident: 1480_CR122 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2016.2585504 – ident: 1480_CR92 – volume: 29 start-page: 1640 issue: 18 year: 1993 ident: 1480_CR128 publication-title: Electron Lett doi: 10.1049/el:19931092 – ident: 1480_CR62 doi: 10.1109/EuCAP.2012.6206356 – volume: 2015 start-page: 372124 year: 2015 ident: 1480_CR114 publication-title: Int J Antenn Propag doi: 10.1155/2015/372124 – ident: 1480_CR80 doi: 10.1109/infcomw.2017.8116491 – volume: 13 start-page: 1113 issue: 8 year: 2019 ident: 1480_CR137 publication-title: IET Microw Antenn Propag doi: 10.1049/iet-map.2018.6187 – volume: 35 start-page: 1887 issue: 8 year: 2017 ident: 1480_CR143 publication-title: IEEE J Sel Areas Commun doi: 10.1109/JSAC.2017.2710758 – volume: 67 start-page: 8549 issue: 9 year: 2018 ident: 1480_CR45 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2018.2851783 – volume-title: Theory and Novel Applications of Machine Learning year: 2009 ident: 1480_CR54 – volume: 56 start-page: 102 issue: 6 year: 2014 ident: 1480_CR99 publication-title: IEEE Antenn Propag Mag doi: 10.1109/MAP.2014.7011023 – volume: 66 start-page: 26 issue: 1 year: 2017 ident: 1480_CR85 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2016.2530306 – volume: 68 start-page: 49 issue: 1 year: 2018 ident: 1480_CR123 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2018.2878352 – volume: 60 start-page: 080301 issue: 8 year: 2017 ident: 1480_CR142 publication-title: Sci China Inform Sci doi: 10.1007/s11432-016-9144-x – start-page: 63 volume-title: Advanced Lectures on Machine Learning year: 2003 ident: 1480_CR111 doi: 10.1007/978-3-540-28650-9_4 – volume: 2013 start-page: 378407 year: 2013 ident: 1480_CR77 publication-title: Int J Antenn Propag doi: 10.1155/2013/378407 – volume: 16 start-page: 148 issue: 1 year: 2019 ident: 1480_CR66 publication-title: China Commun – volume-title: Learning from Delayed Rewards year: 1989 ident: 1480_CR132 – volume-title: Wireless Communications year: 2012 ident: 1480_CR90 – ident: 1480_CR42 doi: 10.1109/WCNC.2016.7564890 – ident: 1480_CR102 doi: 10.1109/PIMRC.2018.8580938 – volume: 60 start-page: 33 year: 2017 ident: 1480_CR26 publication-title: Dig Signal Process doi: 10.1016/j.dsp.2016.08.014 – ident: 1480_CR22 – volume: 66 start-page: 897 issue: 2 year: 2017 ident: 1480_CR8 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2016.2563038 – volume: 82 start-page: 35 issue: 1 year: 1960 ident: 1480_CR55 publication-title: J Bas Eng doi: 10.1115/1.3662552 – ident: 1480_CR125 doi: 10.1109/WCNC.2009.4917538 – ident: 1480_CR17 doi: 10.23919/EuCAP.2017.7928124 – volume-title: IMT Traffic Estimates for the Years 2020 to 2030 year: 2015 ident: 1480_CR48 – volume: 60 start-page: 833 issue: 3 year: 2012 ident: 1480_CR50 publication-title: IEEE Trans Microw Theory Technol doi: 10.1109/TMTT.2011.2178859 – volume: 13 start-page: 14 issue: S2 year: 2016 ident: 1480_CR140 publication-title: China Commun doi: 10.1109/CC.2016.7833457 – volume: 20 start-page: 3142 issue: 4 year: 2018 ident: 1480_CR129 publication-title: IEEE Commun Surv Tutor doi: 10.1109/COMST.2018.2862141 – volume: 1 start-page: 81 issue: 1 year: 1986 ident: 1480_CR107 publication-title: Mach Learn – volume: 18 start-page: 753 issue: 6 year: 2017 ident: 1480_CR5 publication-title: Front Inform Technol Electron Eng doi: 10.1631/FITEE.1601817 – ident: 1480_CR120 doi: 10.1109/WCNC.2018.8377337 – ident: 1480_CR11 doi: 10.1109/glocomw.2018.8644245 – volume: 6 start-page: 1654 issue: 2 year: 2019 ident: 1480_CR18 publication-title: IEEE Int Things J doi: 10.1109/JIOT.2018.2874816 – ident: 1480_CR97 doi: 10.1109/EuCAP.2014.6902475 – ident: 1480_CR61 – ident: 1480_CR75 doi: 10.1109/VETEC.1996.501466 – ident: 1480_CR7 doi: 10.1109/GLOCOM.2014.7037248 – ident: 1480_CR84 doi: 10.1109/DASC.2014.6979495 – ident: 1480_CR88 – volume: 5 start-page: 2126 year: 2017 ident: 1480_CR14 publication-title: IEEE Access doi: 10.1109/ACCESS.2017.2652983 – ident: 1480_CR46 – ident: 1480_CR78 doi: 10.1109/RWS.2011.5725435 – volume: 40 start-page: 375 issue: 2 year: 1991 ident: 1480_CR79 publication-title: IEEE Trans Veh Technol doi: 10.1109/25.289418 – volume: 6 start-page: 6820 year: 2018 ident: 1480_CR70 publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2793298 – ident: 1480_CR87 doi: 10.1109/MILCOM.2005.1606122 – volume: 12 start-page: 119 issue: 1 year: 2018 ident: 1480_CR93 publication-title: IEEE J Sel Top Signal Process doi: 10.1109/JSTSP.2017.2788405 – volume: 66 start-page: 282 issue: 1 year: 2017 ident: 1480_CR74 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2016.2542106 – volume: 41 start-page: 1002 issue: 18 year: 2005 ident: 1480_CR100 publication-title: Electron Lett doi: 10.1049/el:20052444 – ident: 1480_CR3 – volume-title: Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2017–2022 White Paper year: 2019 ident: 1480_CR19 – ident: 1480_CR117 doi: 10.1109/SICON.2005.257875 – volume: 7 start-page: 2740 issue: 7 year: 2008 ident: 1480_CR124 publication-title: IEEE Trans Wirel Commun doi: 10.1109/TWC.2008.070143 – ident: 1480_CR96 doi: 10.1109/EuCAP.2016.7481470 – ident: 1480_CR118 doi: 10.1109/MWC.001.1900323 – volume: 9 start-page: 1735 issue: 7 year: 1997 ident: 1480_CR41 publication-title: Neur Comput doi: 10.1162/neco.1997.9.8.1735 – volume: 49 start-page: 744 issue: 3 year: 2000 ident: 1480_CR136 publication-title: IEEE Trans Veh Technol doi: 10.1109/25.845094 – volume: 11 start-page: 62 issue: 1 year: 2016 ident: 1480_CR71 publication-title: IEEE Syst J doi: 10.1109/JSYST.2015.2477503 – ident: 1480_CR83 – volume-title: Recommendation year: 2013 ident: 1480_CR47 – volume: 20 start-page: 561 issue: 3 year: 2011 ident: 1480_CR119 publication-title: Radioengineering – volume: 37 start-page: 1554 issue: 6 year: 1966 ident: 1480_CR10 publication-title: Ann Math Stat doi: 10.1214/aoms/1177699147 – ident: 1480_CR44 doi: 10.1109/IMCCC.2016.123 – volume: 23 start-page: 1015 issue: 19 year: 1987 ident: 1480_CR109 publication-title: Electron Lett doi: 10.1049/el:19870712 – volume: 36 start-page: 104 issue: 1 year: 1988 ident: 1480_CR127 publication-title: IEEE Trans Antenn Propag doi: 10.1109/8.1081 – volume: 35 start-page: 1030 issue: 5 year: 2017 ident: 1480_CR131 publication-title: IEEE J Sel Area Commun doi: 10.1109/JSAC.2017.2679660 – volume: 52 start-page: 42 issue: 12 year: 2014 ident: 1480_CR24 publication-title: IEEE Commun Mag doi: 10.1109/MCOM.2014.6979985 – volume: 21 start-page: 2361 issue: 3 year: 2019 ident: 1480_CR59 publication-title: IEEE Commun Surv Tutor doi: 10.1109/COMST.2019.2915069 – volume: 29 start-page: 290 issue: 2 year: 1980 ident: 1480_CR40 publication-title: IEEE Trans Veh Technol doi: 10.1109/T-VT.1980.23854 – volume: 20 start-page: 2714 issue: 4 year: 2018 ident: 1480_CR72 publication-title: IEEE Commun Surv Tutor doi: 10.1109/COMST.2018.2841996 – ident: 1480_CR6 – ident: 1480_CR112 doi: 10.1109/ICUMT.2017.8255203 – volume: 5 start-page: 194 issue: 5 year: 2001 ident: 1480_CR67 publication-title: IEEE Commun Lett doi: 10.1109/4234.922757 – ident: 1480_CR95 doi: 10.1109/MILCOM.2003.1290436 – volume: 56 start-page: 62 issue: 3 year: 2018 ident: 1480_CR144 publication-title: IEEE Commun Mag doi: 10.1109/MCOM.2018.1700846 – ident: 1480_CR39 doi: 10.1049/cp.2018.0453 – ident: 1480_CR21 – ident: 1480_CR73 doi: 10.23919/ICACT.2018.8323708 – volume: 24 start-page: 98 issue: 2 year: 2016 ident: 1480_CR53 publication-title: IEEE Wirel Commun doi: 10.1109/MWC.2016.1500356WC – volume: 35 start-page: 589 issue: 5 year: 1987 ident: 1480_CR36 publication-title: IEEE Trans Antenn Propag doi: 10.1109/TAP.1987.1144137 – volume: 59 start-page: 1688 issue: 5 year: 2011 ident: 1480_CR104 publication-title: IEEE Trans Antenn Propag doi: 10.1109/TAP.2011.2122294 – volume-title: Guidelines for Evaluation of Radio Interface Technologies for IMT-2020 year: 2017 ident: 1480_CR135 – volume: 51 start-page: 254 issue: 2 year: 2002 ident: 1480_CR38 publication-title: IEEE Trans Veh Technol doi: 10.1109/25.994803 – volume: 18 start-page: 773 issue: 6 year: 2017 ident: 1480_CR65 publication-title: Front Inform Technol Electron Eng doi: 10.1631/FITEE.1700021 – ident: 1480_CR29 – volume: 6 start-page: 3028 issue: 8 year: 2007 ident: 1480_CR56 publication-title: IEEE Trans Wirel Commun doi: 10.1109/TWC.2007.051050 – ident: 1480_CR63 doi: 10.1109/PIMRC.2014.7136161 – ident: 1480_CR1 – volume: 12 start-page: 1287 issue: 8 year: 2018 ident: 1480_CR108 publication-title: IET Microw Antenn Propag doi: 10.1049/iet-map.2017.0711 – ident: 1480_CR9 – volume: 6 start-page: 2404 issue: 15 year: 2012 ident: 1480_CR31 publication-title: IET Commun doi: 10.1049/iet-com.2012.0028 – volume: 52 start-page: 218 issue: 6 year: 2014 ident: 1480_CR141 publication-title: IEEE Commun Mag doi: 10.1109/MCOM.2014.6829967 – volume-title: Ericsson Mobility Report year: 2015 ident: 1480_CR13 – ident: 1480_CR58 doi: 10.1109/GLOCOM.2016.7842372 – volume: 15 start-page: 547 issue: 6 year: 2013 ident: 1480_CR105 publication-title: J Commun Netw doi: 10.1109/JCN.2013.000103 – ident: 1480_CR4 – volume: 34 start-page: 1460 issue: 12 year: 1986 ident: 1480_CR126 publication-title: IEEE Trans Antenn Propag doi: 10.1109/TAP.1986.1143781 – volume-title: Architectural Framework for Machine Learning in Future Networks Including IMT-2020. Recommendation Y.3172 year: 2019 ident: 1480_CR49 – volume: 2 start-page: 41 issue: 1 year: 2017 ident: 1480_CR64 publication-title: J Commun Inform Netw doi: 10.1007/s41650-017-0004-z – volume: 49 start-page: 242 issue: 3 year: 2014 ident: 1480_CR106 publication-title: Radio Sci doi: 10.1002/2013RS005292 – ident: 1480_CR25 doi: 10.1109/PIMRC.2018.8580992 – ident: 1480_CR94 doi: 10.1109/ICC.2018.8422221 – ident: 1480_CR138 doi: 10.1109/GLOCOMW.2011.6162389 – volume: 65 start-page: 2637 issue: 4 year: 2015 ident: 1480_CR134 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2015.2419738 – ident: 1480_CR68 doi: 10.1109/WiCOM.2012.6478340 – volume: 4 start-page: 145 issue: 1 year: 2019 ident: 1480_CR145 publication-title: J Commun – volume: 66 start-page: 6607 issue: 8 year: 2017 ident: 1480_CR86 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2017.2659651 – volume-title: Pattern Recognition and Machine Learning year: 2006 ident: 1480_CR12 – ident: 1480_CR98 – volume: 20 start-page: 273 issue: 3 year: 1995 ident: 1480_CR23 publication-title: Mach Learn – volume: 12 start-page: 4445 issue: 9 year: 2013 ident: 1480_CR103 publication-title: IEEE Trans Wirel Commun doi: 10.1109/TWC.2013.072313.121581 – volume: 56 start-page: 1413 issue: 5 year: 2008 ident: 1480_CR51 publication-title: IEEE Trans Antenn Propag doi: 10.1109/TAP.2008.922651 – volume-title: IMT Vision-Framework and Overall Objectives of the Future Development of IMT for 2020 and Beyond. Report M.2083–0 year: 2015 ident: 1480_CR116 – ident: 1480_CR35 doi: 10.1109/GLOCOMW.2015.7414180 – ident: 1480_CR15 doi: 10.1109/VTCFall.2016.7881093 – volume: 17 start-page: 961 issue: 4 year: 2018 ident: 1480_CR16 publication-title: IEEE Trans Mob Comput doi: 10.1109/TMC.2017.2742949 – volume: 20 start-page: 1716 issue: 16 year: 1995 ident: 1480_CR43 publication-title: Opt Lett doi: 10.1364/OL.20.001716 – volume: 14 start-page: 421 issue: 2 year: 2008 ident: 1480_CR101 publication-title: IEEE J Sel Top Quant Electron doi: 10.1109/JSTQE.2007.910984 – ident: 1480_CR81 doi: 10.1109/GLOCOMW.2014.7063445 – volume: 4 start-page: 357 issue: 4 year: 2015 ident: 1480_CR115 publication-title: IEEE Wirel Commun Lett doi: 10.1109/LWC.2015.2417559 – ident: 1480_CR20 – volume: 2018 start-page: 9783863 year: 2018 ident: 1480_CR76 publication-title: Wirel Commun Mob Comput doi: 10.1155/2018/9783863 – volume: 2 start-page: 555 issue: 4 year: 1996 ident: 1480_CR91 publication-title: Markov Process Rel Field – ident: 1480_CR139 doi: 10.1109/DASC.2011.6095912 – volume: 65 start-page: 6213 issue: 12 year: 2017 ident: 1480_CR110 publication-title: IEEE Trans Antenn Propag doi: 10.1109/TAP.2017.2734243 – volume: 64 start-page: 3330 issue: 8 year: 2015 ident: 1480_CR60 publication-title: IEEE Trans Veh Technol doi: 10.1109/TVT.2014.2358191 – ident: 1480_CR113 doi: 10.1109/VETECF.2009.5379031 – ident: 1480_CR57 doi: 10.1109/ICC.2016.7511280 – ident: 1480_CR30 doi: 10.1109/VETECS.2006.1683399 – volume: 1 start-page: 462 issue: 2 year: 2011 ident: 1480_CR52 publication-title: IEEE Trans Terahertz Sci Technol doi: 10.1109/TTHZ.2011.2153610 – volume: 9 start-page: 3590 issue: 11 year: 2010 ident: 1480_CR82 publication-title: IEEE Trans Wirel Commun doi: 10.1109/TWC.2010.092810.091092
SSID	ssj0001619798
Score	2.5059123
SecondaryResourceType	review_article
Snippet	With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high... TN929.5; With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands...
SourceID	wanfang proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	39
SubjectTerms	6G mobile communication Commercialization Communications Engineering Communications networks Computer Hardware Computer Science Computer Systems Organization and Communication Networks Electrical Engineering Electronics and Microelectronics Industrial applications Industrial Internet of Things Instrumentation Internet of Things Machine learning Network latency Networks New technology Propagation R&D Research & development Review Technology Trends Wireless communication systems Wireless communications
SummonAdditionalLinks	– databaseName: ProQuest Central dbid: BENPR link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3fS8MwED7m9qIP4k-cTgko-mK1SZs2FURUNqfgEHGwt5I2iSCzm26D4V9v0qZWH-Zzjxbu0rvvLnf3ARxRSajpTnQ0umCOzzl3OA2VI5OQYkUZF3nB7bEXdPv-w4AOatArZ2FMW2XpE3NHLUapqZGfkwizkGj4ja_GH45hjTK3qyWFBrfUCuIyXzG2BA3tkqlbh8ZNu_f0XFVddL4Q5gS5xM1JCplvF28GHj7vaG_RPtMhUuMc92-gqtDnz4VpPuaTKZ69_opInTVYtVASXRe2X4eazDZg5deCwU24N8MDmRyi96oUOEE8EyhnwJkgDVlRcHeB0mJNEzLzRbNCotg2gkzHkAbiW9DvtF9uu44lT3BSz4umjtBeTAjf5SJKKJaC0YBFSni-1Dkfc5VJnGiaRpH0QuYmghg7UaYYVsIXknjbUM9GmdwB5EupgQUj0uRTJFSRFyQeVjgI3cRw3DThtNRUnNrN4obgYhibDEMrNs4VG1vFNuH4R3xcrNRYJNgq1R7bP2sSV-egCSelKarHC150aC1VCX69ifk8SWNJXNNWpp3R7v-f24NlI1qUX1pQn37O5L4GJNPkwJ6yb6C52zk priority: 102 providerName: ProQuest
Title	Channel measurements and models for 6G: current status and future outlook
URI	https://link.springer.com/article/10.1631/FITEE.1900450 https://www.proquest.com/docview/2918726261 https://d.wanfangdata.com.cn/periodical/zjdxxbc-e202001005
Volume	21
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
link	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LS8NAEB60XvTgW6yPsqDoxdRkk0023qw09YFFREFPIcnuClqj2Bakv97ZZGOrIugph2yWZGdm9_sm8wDYZZIyHZ1oIbrglpckiZWwQFkyDZijGE9E4XC77Pqnt975HbubgsMqF6aIdq9-SRY7tTZr33UOIzTldhPPLwQhyNFnGHITtMSZ4879xYRbBQlBUHTApXbRhZB7prLmjzm-nkRjePn5R7TI48lVkj9MHDnRAlxVL1tGmjw1h4O0mY2-1XH8x9cswryBn-S41JclmJL5MixUrR2IsfRlmJuoU7gCZzoHIZc98jz2KPZJkgtSNNLpE0S-xO8ckays9kR0mtKwHFEWLSE68Ajx_CrcRu2bk1PL9GCwMtcNB5bAzVAIz05EmDJHCs58HirhehKpI7eV5l8sy8JQugG3U0G1uBlX3FHCE5K6a1DLX3K5DsSTEvEJp1LTMhqo0PVT11GOH9ipbpVTh4NKHnFmCpTrPhm9WBMVXLS4WLTYLFod9j6Hv5aVOX4buFUJNzYG2o8pakZAkc05ddivJDS-_ctEO0YfxgNHj-L9Pc1iSW0dnYZ72saf59uEWf1U6dDZgtrgbSi3EeIM0gZM86jTQOWOWq1uwyg5Xlvt7tX1B9Bp9g4
linkProvider	Springer Nature
linkToHtml	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LT9wwEB6h5UB7QPSlLtBiqQ8uBBInThwkhCjd7W6BVYVA4hac2EZCEB67qNAf19_GTOIQeqA3zrETZWzPfDOemQ_gszBcUHaih-hCepFSylMisZ7JExFYIZWuAm57o3hwGP08EkdT8LephaG0ykYnVopaXxQUI1_jaSATjvA72Ly88og1im5XGwoN5agV9EbVYswVduyYu9_owo03ht9xvb9w3u8dbA88xzLgFWGYTjyNx13ryFc6zUVgtBSxTK0OI4POkfQteRiiKNLUhIn0c83ph4S0MrA60oYaH6AJmI4ogNKB6W-90a_9NsqDs5OKkJf7FSmijFyjzzgM1vqonXqraJIRV_n_GsYW7T5c0FZlRaVV5ckjC9ifg1kHXdlWvddewZQpX8PLRw0N38CQihVKc8bO29DjmKlSs4pxZ8wQIrP4xzor6rZQjOqZbuoRdXcTRhlKCPzfwuGziPEddMqL0rwHFhmDQEZyQ_4bT2waxnkY2CBO_Jw4dbqw0kgqK1wncyLUOMvIo0HBZpVgMyfYLnx9GH5Zt_B4auBiI_bMneRx1u67Liw3S9E-fuJFn9xKtQP_nOrb27zIDPcpjQ2V3_z_P7cEM4ODvd1sdzjaWYAXNK0O_SxCZ3J9Yz4gGJrkH92OY3D83Jv8HlckGH8
linkToPdf	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3fS8MwED7GBqIP_hbnz4CiL3Zr06ZN9Wno5uZ0-KCgIJS2SQSddbgOxL_epE3dVAbic4_QJpfku-vd9wHsE46Jqk40JLqghhOGoRESTxg88oglCA1ZlnC76rntW-fijtyV4KTohcmq3YtfknlPg2JpStL6gIlsi7u2VW_Jbd2sybtMAhIZr1ccJR9Rhkrj_L47kWKRwYGXqeFiM1MkpI5m2fw1xvdbaQw1v_6OZj09iQiTx4nrp7UAD8WL51Unz7VRGtXijx-cjv_8skWY17AUNXI_WoIST5ZhoZB8QPoEWIa5Cf7CFeio3oSE99HLONM4RGHCUCawM0QSESP3_BjFOQsUUu1Lo9wiJzNBqiBJ4vxVuG01b07bhtZmMGLb9lODyUOSMccMmR8RizNKXOoLZjtchpTUFCouI3Hs-9z2qBkxrNyAUEEtwRzGsb0G5eQ14euAHM4lbqGYq3ANe8K33ci2hOV6ZqQkdKpwVKxNEGvicqWf0Q9UACMnLcgmLdCTVoWDL_NBztgxzXCrWOhAb9xhgKWXeFhGeVYVDovVGj-eMtCe9o2x4ccTe3-P4oBjU1WtybNu48_j7cLM9VkruOz0upswqwbIcz5bUE7fRnxboqA02tHe_gm0IP3e
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Channel+measurements+and+models+for+6G%3Acurrent+status+and+future+outlook&rft.jtitle=%E4%BF%A1%E6%81%AF%E4%B8%8E%E7%94%B5%E5%AD%90%E5%B7%A5%E7%A8%8B%E5%89%8D%E6%B2%BF%EF%BC%88%E8%8B%B1%E6%96%87%E7%89%88%EF%BC%89&rft.au=Jian-hua+ZHANG&rft.au=Pan+TANG&rft.au=Li+YU&rft.au=Tao+JIANG&rft.date=2020&rft.pub=State+Key+Lab+of+Networking+and+Switching+Technology%2CBeijing+University+of+Posts+and+Telecommunications%2CBeijing+100876%2CChina&rft.issn=2095-9184&rft.volume=21&rft.issue=1&rft.spage=39&rft.epage=61&rft_id=info:doi/10.1631%2FFITEE.1900450&rft.externalDocID=zjdxxbc_e202001005
thumbnail_s	http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fzjdxxbc-e%2Fzjdxxbc-e.jpg