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  • 标题:Comparative Analysis of Time and Frequency Division Spectrum Sensing Frameworks in Cognitive Radio Network
  • 本地全文:下载
  • 作者:O.P. Meena ; Ajay Somkuwar ; Tarun Kumar Gupta
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2017
  • 卷号:17
  • 期号:2
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:This paper provides comparative analysis of time and frequency division based spectrum sensing frameworks for single channel point to point communication links in Cognitive Radio Network (CRN). In Time Division Spectrum Sensing Frameworks (TDSSF) the unlicensed (secondary) user senses the spectrum periodically. The periodic sensing interrupts secondary user��s (SU��s) data transmission which results in its low throughput and also leads to high missed detection probability which causes interference to the licensed (primary) users. To address the limitations of the TDSSF, a Frequency Division Spectrum Sensing Frameworks (FDSSF) may be used which supports continuous spectrum sensing. In FDSSF a part of the spectrum is used for continuous spectrum sensing and the remaining part of the spectrum is used for SU data transmission. The simulation results show that for target probability of detection 0.5, throughput-oriented-FDSSF for K=2 gives 1.45 dB, 5.2 dB and 5.65 dB primary user��s SNR gains over delay-oriented-FDSSF, multi-slot-TDSSF and single-slot-TDSSF respectively. In perspective of SU throughput for SU��s SNR= 5 dB, throughput-oriented-FDSSF gives 9.09%, 30.6% and 36.92% higher throughput as compare to delay-oriented-FDSSF, multi-slot-TDSSF and single-slot-TDSSF respectively.
  • 关键词:Cognitive radio network; spectrum sensing framework; detection probability; false alarm probability; throughput.
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