SLEEPING CELL DETECTION
An apparatus, method and computer program is described, comprising: obtaining initial training labels for first performance management data of a mobile communication network, wherein the initial training labels are generated by a first classification model to identify potentially sleeping cells of t...
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| creator | PINA, Alessia TIOZZO, Annagiulia GEMELLI, Riccardo CORBETTA, Giuliano |
| description | An apparatus, method and computer program is described, comprising: obtaining initial training labels for first performance management data of a mobile communication network, wherein the initial training labels are generated by a first classification model to identify potentially sleeping cells of the mobile communication network; training a machine-learning model based on the initial training labels, wherein the model is configured to identify potentially sleeping cells within the mobile communication network; identifying potentially sleeping cells using the trained machine-learning model based on second performance management data of the mobile communication network; receiving feedback based on an impact of corrective action taken based on the identification, by the machine-learning model, of said potentially sleeping cells; updating said training labels based on said received feedback; and retraining the machine-learning model based on the updated training labels. |
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training a machine-learning model based on the initial training labels, wherein the model is configured to identify potentially sleeping cells within the mobile communication network; identifying potentially sleeping cells using the trained machine-learning model based on second performance management data of the mobile communication network; receiving feedback based on an impact of corrective action taken based on the identification, by the machine-learning model, of said potentially sleeping cells; updating said training labels based on said received feedback; and retraining the machine-learning model based on the updated training labels.</description><language>eng ; fre ; ger</language><subject>ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRICITY ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION ; WIRELESS COMMUNICATIONS NETWORKS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211020&DB=EPODOC&CC=EP&NR=3896905A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211020&DB=EPODOC&CC=EP&NR=3896905A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>PINA, Alessia</creatorcontrib><creatorcontrib>TIOZZO, Annagiulia</creatorcontrib><creatorcontrib>GEMELLI, Riccardo</creatorcontrib><creatorcontrib>CORBETTA, Giuliano</creatorcontrib><title>SLEEPING CELL DETECTION</title><description>An apparatus, method and computer program is described, comprising: obtaining initial training labels for first performance management data of a mobile communication network, wherein the initial training labels are generated by a first classification model to identify potentially sleeping cells of the mobile communication network; training a machine-learning model based on the initial training labels, wherein the model is configured to identify potentially sleeping cells within the mobile communication network; identifying potentially sleeping cells using the trained machine-learning model based on second performance management data of the mobile communication network; receiving feedback based on an impact of corrective action taken based on the identification, by the machine-learning model, of said potentially sleeping cells; updating said training labels based on said received feedback; and retraining the machine-learning model based on the updated training labels.</description><subject>ELECTRIC COMMUNICATION TECHNIQUE</subject><subject>ELECTRICITY</subject><subject>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><subject>WIRELESS COMMUNICATIONS NETWORKS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZBAP9nF1DfD0c1dwdvXxUXBxDXF1DvH09-NhYE1LzClO5YXS3AwKbq4hzh66qQX58anFBYnJqXmpJfGuAcYWlmaWBqaOhsZEKAEAkwMfDA</recordid><startdate>20211020</startdate><enddate>20211020</enddate><creator>PINA, Alessia</creator><creator>TIOZZO, Annagiulia</creator><creator>GEMELLI, Riccardo</creator><creator>CORBETTA, Giuliano</creator><scope>EVB</scope></search><sort><creationdate>20211020</creationdate><title>SLEEPING CELL DETECTION</title><author>PINA, Alessia ; 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| language | eng ; fre ; ger |
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| subjects | ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION WIRELESS COMMUNICATIONS NETWORKS |
| title | SLEEPING CELL DETECTION |
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