Intelligent Spectrum Sensing and Resource Allocation in Cognitive Networks via Deep Reinforcement Learning

Dinh C. Nguyen, David J. Love, Christopher G. Brinton

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Opportunistic spectrum access is a viable technique for cognitive radio (CR) networks to address the spectrum scarcity problem, where both spectrum sensing and resource allocation (SSRA) are significant to the system throughput performance. Previous works on SSRA often require complete network statistics which may not be feasible given the time-varying nature of practical CR networks. In this paper, we propose a learning-based optimization framework for SSRA in multi-band-multi-user CR networks. We develop a dynamic cooperative spectrum sensing strategy which allows secondary users to detect available spectrum bands of the primary user, followed by flexible power allocation for efficient data transmissions. To cope with the dynamic of channel and resource statistics, we propose an improved deep reinforcement learning scheme based on a maximum entropy-enabled actor critic algorithm. Numerical results demonstrate the superiority of our approach over existing schemes.

Original languageEnglish (US)
Title of host publicationICC 2023 - IEEE International Conference on Communications
Subtitle of host publicationSustainable Communications for Renaissance
EditorsMichele Zorzi, Meixia Tao, Walid Saad
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538674628
StatePublished - 2023
Externally publishedYes
Event2023 IEEE International Conference on Communications, ICC 2023 - Rome, Italy
Duration: May 28 2023Jun 1 2023

Publication series

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


Conference2023 IEEE International Conference on Communications, ICC 2023

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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