Secondary User Power Control Aided Cooperative Spectrum Sensing

Bin SHEN; Zhiqiang WANG; Han QING

doi:10.11999/JEIT171232

Volume 40 Issue 10

Sep. 2018

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Bin SHEN, Zhiqiang WANG, Han QING. Secondary User Power Control Aided Cooperative Spectrum Sensing[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2337-2344. doi: 10.11999/JEIT171232

Citation:

Bin SHEN, Zhiqiang WANG, Han QING. Secondary User Power Control Aided Cooperative Spectrum Sensing[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2337-2344. doi: 10.11999/JEIT171232

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Secondary User Power Control Aided Cooperative Spectrum Sensing

doi: 10.11999/JEIT171232

Chongqing Key Laboratory of Mobile Communications, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The Municipal Natural Science Foundation of Chongqing (cstc2016jcyjA0595)

Received Date: 2017-12-18
Rev Recd Date: 2018-05-23

Available Online: 2018-07-30

Publish Date: 2018-10-01

Abstract

Abstract

In conventional cooperative spectrum sensing, the signal model is usually simplified as a single-stage channel environment where the Secondary Users (SUs) collect their spectrum data and report to the Fusion Center (FC) with the same transmit power. This hampers the FC from efficiently exploiting the space diversity gain beneath the data of different users. In order to solve this problem and control the user transmit power in reporting their data, three Optimal Power Control (OPC) schemes are proposed. When the Channel Statistic (CS) of the sensing channel and the reporting channel are perfectly known at the FC, a CS Aided Optimal Power Control (CSA-OPC) scheme is derived in closed-form, whereas when the CS is practically unavailable, Principal EigenVector aided OPC (PEV-OPC) and Blindly Weighted Multiple-EigenVector aided OPC (BWMEV-OPC) schemes are developed. Theoretical analysis and computer simulation verify that the propose OPC schemes greatly ameliorate the spectrum sensing performance, compared to the non-OPC aided cooperative spectrum sensing schemes.
- Cognitive Radio (CR),
- Cooperative Spectrum Sensing (CSS),
- Power control,
- Optimal power control vector

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References(16)

References

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