• DocumentCode
    3861241
  • Title

    Dynamic Packet Size Optimization and Channel Selection for Cognitive Radio Sensor Networks

  • Author

    Amna Jamal;Chen-Khong Tham;Wai-Choong Wong

  • Author_Institution
    Department of Electrical and Computer Engineering, National University of Singapore, Singapore
  • Volume
    1
  • Issue
    4
  • fYear
    2015
  • Firstpage
    394
  • Lastpage
    405
  • Abstract
    Dynamic spectrum access has gained traction in wireless sensor networks (WSNs) because of the scarcity in spectrum caused by the proliferation of wireless devices and services, and it provides spectrum efficient communication for the WSNs. However, the communication between nodes in a cognitive radio sensor network (CRSN) is affected by the transmission power, fading, and interference with licensed users, and these factors hinder the data transmission between the energy constrained cognitive radio sensor nodes. Therefore, there is a need for an adaptive energy-efficient optimization scheme which takes into account the varying environment conditions. Since packet length plays a pivotal role in determining the performance of the network, packet size adaptation that is aware of the channel characteristics may bring about performance improvement. Furthermore, existing packet size optimization or channel selection schemes devised for WSNs and CR networks are not appropriate for the CRSN framework. In this paper, we devise a dynamic packet size optimization and channel selection scheme (DyPSOCS) for CRSNs. We employ a constrained Markov decision process (CMDP) to solve the optimization problem with quality of service (QoS) constraints. Simulation results show improvement in QoS performance as well as energy efficiency when compared to other schemes.
  • Keywords
    "Optimization","Wireless sensor networks","Cognitive radio","Interference","Media Access Protocol","Bit error rate","Delays"
  • Journal_Title
    IEEE Transactions on Cognitive Communications and Networking
  • Publisher
    ieee
  • Electronic_ISBN
    2332-7731
  • Type

    jour

  • DOI
    10.1109/TCCN.2016.2531082
  • Filename
    7410030