DEEP LEARNING-BASED USER CLUSTERING IN MILLIMETER WAVE NON-ORTHOGONAL MULTIPLE ACCCESS COMMUNICATIONS

A method and network node for deep learning based user clustering in millimeter wave (mmWave) non-orthogonal multiple access (NOMA) are disclosed. According to one aspect, a method includes determining a minimum number of clusters to be served by the network node subject to a first constraint that l...

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Bibliographic Details
Main Authors SOKUN, Hamza, YANIKOMEROGLU, Halim, RAJASEKARAN, Aditya Sriram, MARAQA, Omar, AL-AHMADI, Saad
Format Patent
LanguageEnglish
Published 29.02.2024
Subjects
ANALOGOUS ARRANGEMENTS USING OTHER WAVES
DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES
MEASURING
MULTIPLEX COMMUNICATION
PHYSICS
RADIO DIRECTION-FINDING
RADIO NAVIGATION
TESTING
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Summary:A method and network node for deep learning based user clustering in millimeter wave (mmWave) non-orthogonal multiple access (NOMA) are disclosed. According to one aspect, a method includes determining a minimum number of clusters to be served by the network node subject to a first constraint that limits a total number of WDs in each cluster. The method also includes assigning WDs to each cluster of the minimum number of clusters while or after the minimum number of clusters is determined, the determined minimum number of clusters and WD assignments being for a first spatial distribution of the plurality of WDs.
Bibliography:Application Number: US202018256467