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Reinforcement Learning-Aided Channel Estimator in Time-Varying MIMO Systems.

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  • المؤلفون: Kim TK;Kim TK; Min M; Min M
  • المصدر:
    Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Jun 18; Vol. 23 (12). Date of Electronic Publication: 2023 Jun 18.
  • نوع النشر :
    Journal Article
  • اللغة:
    English
  • معلومة اضافية
    • المصدر:
      Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: PubMed not MEDLINE; MEDLINE
    • بيانات النشر:
      Original Publication: Basel, Switzerland : MDPI, c2000-
    • الموضوع:
      Algorithms* ; Policy*; Computer Simulation ; Markov Chains
    • نبذة مختصرة :
      This paper proposes a reinforcement learning-aided channel estimator for time-varying multi-input multi-output systems. The basic concept of the proposed channel estimator is the selection of the detected data symbol in the data-aided channel estimation. To achieve the selection successfully, we first formulate an optimization problem to minimize the data-aided channel estimation error. However, in time-varying channels, the optimal solution is difficult to derive because of its computational complexity and the time-varying nature of the channel. To address these difficulties, we consider a sequential selection for the detected symbols and a refinement for the selected symbols. A Markov decision process is formulated for sequential selection, and a reinforcement learning algorithm that efficiently computes the optimal policy is proposed with state element refinement. Simulation results demonstrate that the proposed channel estimator outperforms conventional channel estimators by efficiently capturing the variation of the channels.
    • References:
      Sensors (Basel). 2021 Jul 16;21(14):. (PMID: 34300599)
      Sensors (Basel). 2021 Dec 31;22(1):. (PMID: 35009848)
      Sensors (Basel). 2022 Jun 09;22(12):. (PMID: 35746162)
    • Grant Information:
      2021R1F1A1063273 National Research Foundation of Korea; 2023R1A2C1004034 National Research Foundation of Korea; 4199990113966 Ministry of Education, Korea
    • Contributed Indexing:
      Keywords: data-aided channel estimation; first-order Gaussian—Markov channel model; non-iterative approach; reinforcement learning
    • الموضوع:
      Date Created: 20230708 Date Completed: 20230710 Latest Revision: 20230718
    • الموضوع:
      20231215
    • الرقم المعرف:
      PMC10304914
    • الرقم المعرف:
      10.3390/s23125689
    • الرقم المعرف:
      37420854