A New RF Beam Training Method and Asymptotic Performance Analysis for Multi-User Millimeter Wave Systems

Taeseok Oh, Changick Song, Jaehoon Jung, Minki Ahn, Joonsuk Kim, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


In this paper, we consider a multi-user (MU) radio-frequency (RF) beam training scenario with user selection. We propose a new beam training scheme that alleviates the latency issue in the conventional IEEE 802.11ad by adopting a sequential downlink-downlink transmit sector sweep combination. Then, we analyze the average rate performance of several RF beam training schemes in two different asymptotic scenarios. In addition, we characterize the performance gain of the proposed method over other schemes. Our analytic results confirm that the proposed method achieves the average rate performance of the optimal full-search method in the asymptotic region with much reduced training overhead. It is shown from the simulation results that the proposed scheme outperforms the conventional beam training schemes and achieves a 35% performance gain over the optimal full search scheme when considering the beam training overhead in practical MU millimeter-wave channel environments. We also confirm that our analytical results match well with the numerical results.

Original languageEnglish
Article number8451870
Pages (from-to)48125-48135
Number of pages11
JournalIEEE Access
Publication statusPublished - 2018 Aug 29

Bibliographical note

Funding Information:
This work was supported in part by the Future Combat System Network Technology Research Center program of Defense Acquisition Program Administration and in part by the Agency for Defense Development under Grant UD160070BD.

Publisher Copyright:
© 2013 IEEE.


  • Millimeter wave communication
  • RF beam training
  • asymptotic analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)


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