User Scheduling in Massive MIMO: A Joint Deep Learning and Genetic Algorithm Approach

Mostafa Mohammadkarimi, Mostafa Darabi, Behrouz Maham

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

Due to the limited number of radio frequency (RF) chains in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) receivers using analog beamforming/hybrid beamforming, there is a restriction in scheduling the number of users in each transmission time interval. Therefore, fast and low-complexity user scheduling methods based on the instantaneous channel state information (CSI) are needed. In this paper, we propose novel user scheduling methods based on deep learning (DL) to reduce the size of the search space by using the learning capability of a deep neural network (DNN). We formulate the user scheduling combinatorial optimization problem as a regression problem followed by a user separation procedure through decision boundaries that are learned by a trained DNN. The decision boundaries are used to separate the users into two subsets. Then, one of the subsets is selected to be searched to find the users that maximize the sum-rate capacity. The proposed method can achieve a very low outage probability with a few number of searches. In order to achieve ergodic capacity with lower computation complexity, the proposed method is employed in combination with the genetic algorithm (GA) algorithm to take advantage of intelligent initial population selection. Our simulation results show that the proposed user scheduling methods can offer remarkably low complexity.
Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE 95th Vehicular Technology Conference
Subtitle of host publication (VTC2022-Spring)
Place of PublicationPiscataway
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)978-1-6654-8243-1
ISBN (Print)978-1-6654-8244-8
DOIs
Publication statusPublished - 2022
Event2022 IEEE 95th Vehicular Technology Conference - Helsinki, Finland
Duration: 19 Jun 202222 Jun 2022
Conference number: 95th

Conference

Conference2022 IEEE 95th Vehicular Technology Conference
Abbreviated titleVTC2022-Spring
Country/TerritoryFinland
CityHelsinki
Period19/06/2222/06/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • User scheduling
  • massive MIMO communications
  • hybrid beamforming
  • deep learning
  • Genetic algorithm

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