EP3845023A4 - Enabling wireless network personalization using zone of tolerance modeling and predictive analytics - Google Patents

Enabling wireless network personalization using zone of tolerance modeling and predictive analytics Download PDF

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Publication number
EP3845023A4
EP3845023A4 EP19856044.3A EP19856044A EP3845023A4 EP 3845023 A4 EP3845023 A4 EP 3845023A4 EP 19856044 A EP19856044 A EP 19856044A EP 3845023 A4 EP3845023 A4 EP 3845023A4
Authority
EP
European Patent Office
Prior art keywords
zone
wireless network
predictive analytics
enabling wireless
network personalization
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP19856044.3A
Other languages
German (de)
French (fr)
Other versions
EP3845023A1 (en
Inventor
Rawan ALKURD
Halim Yanikomeroglu
Ibrahim ABU ALHAOL
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Carleton University
Original Assignee
Carleton University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Carleton University filed Critical Carleton University
Publication of EP3845023A1 publication Critical patent/EP3845023A1/en
Publication of EP3845023A4 publication Critical patent/EP3845023A4/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
    • H04W28/24—Negotiating SLA [Service Level Agreement]; Negotiating QoS [Quality of Service]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/06—Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
    • H04W4/08—User group management
EP19856044.3A 2018-08-29 2019-08-29 Enabling wireless network personalization using zone of tolerance modeling and predictive analytics Pending EP3845023A4 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201862724195P 2018-08-29 2018-08-29
PCT/CA2019/051197 WO2020041883A1 (en) 2018-08-29 2019-08-29 Enabling wireless network personalization using zone of tolerance modeling and predictive analytics

Publications (2)

Publication Number Publication Date
EP3845023A1 EP3845023A1 (en) 2021-07-07
EP3845023A4 true EP3845023A4 (en) 2022-06-15

Family

ID=69644788

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19856044.3A Pending EP3845023A4 (en) 2018-08-29 2019-08-29 Enabling wireless network personalization using zone of tolerance modeling and predictive analytics

Country Status (3)

Country Link
EP (1) EP3845023A4 (en)
CA (1) CA3111030A1 (en)
WO (1) WO2020041883A1 (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11736973B2 (en) 2018-08-29 2023-08-22 Carleton University Enabling wireless network personalization using zone of tolerance modeling and predictive analytics
CN111553482B (en) * 2020-04-09 2023-08-08 哈尔滨工业大学 Machine learning model super-parameter tuning method
CN112446097B (en) * 2020-12-03 2023-08-29 武汉第二船舶设计研究所(中国船舶重工集团公司第七一九研究所) Multi-objective optimization method for volume and load of steam generator
CN114004358B (en) * 2021-12-29 2022-06-14 粤港澳大湾区数字经济研究院(福田) Deep learning model training method
WO2024035399A1 (en) * 2022-08-10 2024-02-15 Rakuten Mobile, Inc. A system, method, device, and program for interface management of ai/ml applications over radio access parameters
CN117236788B (en) * 2023-10-30 2024-03-26 水利部珠江水利委员会技术咨询(广州)有限公司 Water resource scheduling optimization method and system based on artificial intelligence

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6775233B1 (en) * 1999-08-31 2004-08-10 Lucent Technologies Inc. Rate processor sharing method and apparatus for scheduling data transmissions in a CDMA wireless communication system
US6785227B1 (en) * 2000-05-11 2004-08-31 Lucent Technologies Inc. Method and apparatus for multi-layer resource management in wireless communications systems
WO2014089765A1 (en) * 2012-12-12 2014-06-19 华为技术有限公司 Method, device and system for service scheduling and service transfer rate controlling

Family Cites Families (6)

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Publication number Priority date Publication date Assignee Title
US7512545B2 (en) 2004-01-29 2009-03-31 At&T Intellectual Property I, L.P. Method, software and system for developing interactive call center agent personas
US8751305B2 (en) 2010-05-24 2014-06-10 140 Proof, Inc. Targeting users based on persona data
JP5320358B2 (en) * 2010-08-24 2013-10-23 株式会社エヌ・ティ・ティ・ドコモ Wireless communication system, base station, and wireless resource allocation method
CN102662764B (en) * 2012-04-25 2015-07-29 梁宏斌 A kind of dynamic cloud computational resource optimizing distribution method based on SMDP
CN102932308B (en) * 2012-11-02 2016-07-27 重庆邮电大学 Mixed service Scene dispatch method and dispatching patcher in a kind of OFDM relay system
WO2014127280A2 (en) * 2013-02-14 2014-08-21 Huawei Technologies Co., Ltd. System and method for network resource allocation considering user experience, satisfaction and operator interest

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6775233B1 (en) * 1999-08-31 2004-08-10 Lucent Technologies Inc. Rate processor sharing method and apparatus for scheduling data transmissions in a CDMA wireless communication system
US6785227B1 (en) * 2000-05-11 2004-08-31 Lucent Technologies Inc. Method and apparatus for multi-layer resource management in wireless communications systems
WO2014089765A1 (en) * 2012-12-12 2014-06-19 华为技术有限公司 Method, device and system for service scheduling and service transfer rate controlling

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
See also references of WO2020041883A1 *
YAN JIANGZHOU ET AL: "Resource allocation and admission control based on flow congestion probability in MPLS networks", ADVANCED COMMUNICATION TECHNOLOGY, 2009. ICACT 2009. 11TH INTERNATIONAL CONFERENCE ON, GIRI, PISCATAWAY, NJ, USA, 15 February 2009 (2009-02-15), pages 694 - 697, XP031446199, ISBN: 978-89-5519-138-7 *

Also Published As

Publication number Publication date
EP3845023A1 (en) 2021-07-07
CA3111030A1 (en) 2020-03-05
WO2020041883A1 (en) 2020-03-05

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