Q-learning based superposed band detection in multicarrier transmission

Ali B. Al-Shaikh, Fereidoun H. Panahi, Tomoaki Ohtsuki, Kouhei Suzaki, Hirofumi Sasaki, Hideya So, Tadao Nakagawa

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


Superposed multicarrier transmission is a known method to improve frequency utilization efficiency when several wireless systems share the same spectrum. Obviously, an enhanced spectral efficiency comes at the expense of interference. To suppress the effect of interference, forward error correction (FEC) metric masking can be applied. In FEC, the corresponding log-likelihood (LLR) of the superposed band is set to zero or to other proper values determined by the other parameters such as the desired to undesired power ratio (DUR). To be able to apply the FEC metric masking, the information on the superposed band sub-carriers is required at the receiver side. Therefore, in this paper, we propose a novel method for detecting the superposed bands of multicarrier transmissions using Q-learning. We present the simulation results that show a higher rate of superposed band detection accuracy in lower DUR over the conventional method, as well as similar accuracy over other DUR.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Communications, ICC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467389990
Publication statusPublished - 2017 Jul 28
Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
Duration: 2017 May 212017 May 25


Other2017 IEEE International Conference on Communications, ICC 2017

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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