Machine learning assisted cell association for two-tier communication networks Iki katmanli iletişim aǧlari için makine öǧrenimi destekli hücre ilişkilendirme


Ucas H. R., YÜKSEKKAYA B.

29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021, Virtual, Istanbul, Turkey, 9 - 11 June 2021 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu53274.2021.9477802
  • City: Virtual, Istanbul
  • Country: Turkey
  • Keywords: neural networks, 5G, ultra dense heteregenous networks, user-cell association, 5G
  • Hacettepe University Affiliated: Yes

Abstract

© 2021 IEEE.With the widespread use of fifth generation (5G) mobile communication networks, a much faster increase is expected in the already intense data traffic. This increasing need for traffic will bring along some problems. Ultra dense heterogeneous networks are seen as a solution for 5G communication system requirements and are expected to form the basis of these networks. In this study, a new optimization problem is proposed to associate users with cells in ultra dense heterogeneous networks, and the problem is solved with the help of our own neural network. After the users were associated with the cells, the accuracy and speed performance of the proposed method were compared with brute force solution.