Advanced spectrum sensing for OFDM-based cognitive radio networks using cyclic prefix

Wen Long Chin, Chun Wei Kao, Trong Nghia Le

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

Orthogonal frequency-division multiplexing (OFDM) is a popular transmission technology in cognitive radio (CR) networks, because the correlation of cyclic prex (CP) in OFDM signals can be utilized to improve the reliability of spectrum sensing of secondary users (SUs). However, the optimal spectrum sensing over multipath fading channels remains an important and challenging issue. Therefore, this work proposes an optimal Neyman- Pearson (NP) detector for spectrum sensing using CP. To detect the OFDM signal of primary users (PUs), the log- likelihood ratio (LR) test is formulated by using the correlation characteristics of the redundancy of CP. Analytical results indicate that the LR of received samples is equivalent to their log- likelihood function (LF) plus LR of an energy detector (ED), subsequently allowing us to gain insights on the optimal NP detector. Since many unknown parameters need to be resolved, a practical generalized log-likelihood ratio test (GLRT) is presented. Moreover, to achieve a good performance over multipath fading channels, a channel- independent GLRT (CI-GLRT) is employed to derive an estimation of correlation coefcient independent of multipath channel proles. Simulations conrm the advantages of the proposed detectors compared with state-of-the-art detectors.

原文English
主出版物標題2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781479944491, 9781479944491
DOIs
出版狀態Published - 2014 十一月 24
事件80th IEEE Vehicular Technology Conference, VTC 2014-Fall - Vancouver, Canada
持續時間: 2014 九月 142014 九月 17

出版系列

名字IEEE Vehicular Technology Conference
ISSN(列印)1550-2252

Other

Other80th IEEE Vehicular Technology Conference, VTC 2014-Fall
國家/地區Canada
城市Vancouver
期間14-09-1414-09-17

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 電氣與電子工程
  • 應用數學

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