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  • 标题:AN EFFICIENT RESOURCE ALLOCATION SCHEME IN 5G CRN WITH MULTI – AGENT GAME THEORY APPROACH
  • 本地全文:下载
  • 作者:Baburao Kodavati ; Madhu Ramarakula
  • 期刊名称:International Journal of Early Childhood Special Education
  • 电子版ISSN:1308-5581
  • 出版年度:2022
  • 卷号:14
  • 期号:3
  • 页码:9874-9886
  • DOI:10.9756/INT-JECSE/V14I3.1140
  • 语种:English
  • 出版社:International Journal of Early Childhood Special Education
  • 摘要:Cognitive Radio Networks (CRN)aresubjected to a drastic increase in the number of mobile users. In a conventional CRN network, the spectrum is sensed and transmitted based on the availability of the channel in the CRN network for 5G. With the effective evaluation of the available spectrum of the bands in CRN resources can be effectively utilized. In a CRN environment transmission is performed by both Primary Users (PU) and Secondary Users (SU) for effective utilization of the available spectrum. However, with the increase in the number of users effective Quality of Service (QoS) needs to be achieved. To achieve the desiredresource allocation between primary and secondary users game theory is applied. This paper proposed a multi-agent game theory (MAGT) for the effective allocation of resources between primary and secondary users. The developed MAGT incorporates symmetric form game theory for effective estimation of available resources. The proposed MAGT performance is comparatively examined for different parameters such as Blocking probability, Dropping probability, Channel probability, an acceptance probability. Simulation analysis of proposed MAGT is comparatively examined with existing techniques in CRN. The simulation results stated that the performance of the proposed MAGT exhibits significant performance in terms of improved spectrum utilization frequency through reduced latency with increased throughput. Also, the proposed MAGT effectively improves the channel utilization rate for secondary users rather than conventional users.
  • 关键词:Cognitive Radio Network (CRN);Primary Users (PU);Secondary Users (SU);Multi-agent Game Theory (MAGT);Blocking Probability;Dropping Probability
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