Transfer Learning for Mixed-Integer Resource Allocation Problems in Wireless Networks

Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

9 Citations (Scopus)


Effective resource allocation plays a pivotal role in wireless networks. Unfortunately, typical resource allocation problems are mixed-integer nonlinear programming (MINLP) problems, which are NP-hard. Machine learning based methods recently emerge as a disruptive way to obtain near-optimal performance for MINLP problems with affordable computational complexity. However, they suffer from severe performance deterioration when the network parameters change, which commonly happens in practice and can be characterized as the task mismatch issue. In this paper, we propose a transfer learning method via self-imitation, to address this issue for effective resource allocation in wireless networks. It is based on a general "learning to optimize" framework for solving MINLP problems. A unique advantage of the proposed method is that it can tackle the task mismatch issue with a few additional unlabeled training samples, which is especially important when transferring to large-size problems. Numerical experiments demonstrate that the proposed method, with much less training time, achieves comparable performance with the model trained from scratch based on sufficient labeled samples. To the best of our knowledge, this is the first work that applies transfer learning for resource allocation in wireless networks.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538680889
Publication statusPublished - 20 May 2019
Event2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China
Duration: 20 May 201924 May 2019

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607


Conference2019 IEEE International Conference on Communications, ICC 2019

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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