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A Spectrum-Aware Priority-Based Link Scheduling Algorithm for Cognitive Radio Body Area Networks.

Thien Thi Thanh Le1, Sangman Moh2

  • 1School of Computing and Information Technology, Eastern International University, Hoa Phu, Binh Duong City 75114, Vietnam. thanhthien92003@yahoo.com.

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Summary

This study introduces a spectrum-aware priority-based link scheduling (SPLS) algorithm for cognitive radio body area networks (CRBANs) in hospitals. SPLS enhances data transmission reliability and efficiency, improving patient healthcare services.

Keywords:
cognitive radiocognitive radio body area networklink schedulingwireless body area network

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Area of Science:

  • Wireless communication
  • Medical informatics
  • Network engineering

Background:

  • Wireless Body Area Networks (WBANs) are crucial for medical applications.
  • Interference in hospitals leads to high packet drop rates and latency, impacting patient care.
  • Cognitive radio (CR) offers efficient spectrum sharing for wireless resources.

Purpose of the Study:

  • To propose a Spectrum-Aware Priority-based Link Scheduling (SPLS) algorithm for Cognitive Radio Body Area Networks (CRBANs).
  • To address interference and improve performance in hospital environments.
  • To enhance reliability and efficiency of WBANs in healthcare settings.

Main Methods:

  • Developed the SPLS algorithm utilizing three channels: DataCh, EDataCh, and CtrlCh.
  • Implemented inter-CRBAN communication for channel state information exchange via CtrlCh.
  • Enabled CRBANs to access licensed and unlicensed spectrum based on traffic demands.

Main Results:

  • The SPLS algorithm demonstrated superior performance compared to conventional schemes.
  • Significant improvements were observed in packet delivery ratio, system throughput, and latency.
  • Enhanced energy efficiency was achieved through intelligent spectrum access.

Conclusions:

  • The proposed SPLS algorithm effectively manages spectrum and prioritizes traffic in CRBANs within hospital settings.
  • SPLS mitigates interference, reduces latency, and increases throughput, benefiting patient monitoring.
  • This approach optimizes wireless resource utilization for reliable healthcare delivery.