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Frontiers of Electrical and Electronic Engineering

ISSN 2095-2732

ISSN 2095-2740(Online)

CN 10-1028/TM

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Front Elect Electr Eng    2012, Vol. 7 Issue (4) : 367-373    https://doi.org/10.1007/s11460-012-0214-y
RESEARCH ARTICLE
An improved cooperative spectrum detection algorithm for cognitive radio
Lei CHEN1, Hongjun WANG1(), Guangguo BI2, Min ZHANG1
1. Department of Information, Electronic Engineering Institute, Hefei 230037, China; 2. National Mobile Communication Research Laboratory, Southeast University, Nanjing 210096, China
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Abstract

The ability to detect the primary user’s signal is one of the main performances for cognitive radio networks. Based on the multi-different-cyclic-frequency characteristics of the cyclostationary primary user’s signal and the cooperation detection advantage of the multi-secondary-user, the paper presents the weighted cooperative spectrum detection algorithm based on cyclostationarity in detail. The core of the algorithm is to detect the primary user’s signal by the secondary users’ cooperation detection to the multi-different-cyclic-frequency, and to make a final decision according to the fusion data of the independent secondary users’ detection results. Meanwhile, in order to improve the detection performance, the paper proposes a method to optimize the weight on basis of the deflection coefficient criterion. The result of simulation shows that the proposed algorithm has better performance even in low signal-to-noise ratio (SNR).
Keywords cyclostationary detection      deflection coefficient      weight optimization      cooperative detection     
Corresponding Author(s): WANG Hongjun,Email:hongjun-wang@163.com   
Issue Date: 05 December 2012
 Cite this article:   
Lei CHEN,Hongjun WANG,Guangguo BI, et al. An improved cooperative spectrum detection algorithm for cognitive radio[J]. Front Elect Electr Eng, 2012, 7(4): 367-373.
 URL:  
https://academic.hep.com.cn/fee/EN/10.1007/s11460-012-0214-y
https://academic.hep.com.cn/fee/EN/Y2012/V7/I4/367
Fig.1  Block diagram of MDCF-WCD algorithm
Fig.1  Block diagram of MDCF-WCD algorithm
Fig.1  Block diagram of MDCF-WCD algorithm
Fig.1  Block diagram of MDCF-WCD algorithm
Fig.1  Block diagram of MDCF-WCD algorithm
parametersvalue
sub-carrier modulation modequadrature phase shift keying (QPSK)
FFT lengthNfft = 128
number of occupied channelsNOOC = 128
guard interval lengthNg = 32
symbol rate250 ksym/s
sampling rateRS = 20 MHz
carrier frequencyfc = 5 GHz
Tab.1  OFDM signal parameters in simulation
Fig.2  Single-user detection performance comparison at three different cycle frequencies
Fig.2  Single-user detection performance comparison at three different cycle frequencies
Fig.2  Single-user detection performance comparison at three different cycle frequencies
Fig.2  Single-user detection performance comparison at three different cycle frequencies
Fig.2  Single-user detection performance comparison at three different cycle frequencies
Fig.3  Cooperative detection performance comparison when the detection users are changed
Fig.3  Cooperative detection performance comparison when the detection users are changed
Fig.3  Cooperative detection performance comparison when the detection users are changed
Fig.3  Cooperative detection performance comparison when the detection users are changed
Fig.3  Cooperative detection performance comparison when the detection users are changed
Fig.4  ROC of cooperative detection algorithm proposed in this paper
Fig.4  ROC of cooperative detection algorithm proposed in this paper
Fig.4  ROC of cooperative detection algorithm proposed in this paper
Fig.4  ROC of cooperative detection algorithm proposed in this paper
Fig.4  ROC of cooperative detection algorithm proposed in this paper
Fig.5  Performance comparison of three detection methods
Fig.5  Performance comparison of three detection methods
Fig.5  Performance comparison of three detection methods
Fig.5  Performance comparison of three detection methods
Fig.5  Performance comparison of three detection methods
1 Mitola J, Maguire G Q. Cognitive radio: Making software radios more personal. IEEE Personal Communications , 1999, 6(4): 13–18
doi: 10.1109/98.788210
2 Haykin S. Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications , 2005, 23(2): 201–220
3 Dandawate A V, Giannakis G B. Statistical tests for presence of cyclostationarity. IEEE Transactions on Signal Processing , 1994, 42(9): 2355–2369
doi: 10.1109/78.317857
4 Mosquera C, Scalise S, Lopez-Valcarce R. Non-data-aided symbol rate estimation of linearly modulated signals. IEEE Transactions on Signal Processing , 2008, 56(2): 664–675
doi: 10.1109/TSP.2007.907888
5 Mazet L, Loubaton P H. Cyclic correlation based symbol rate estimation. In: Proceedings of the 33rd Asilomar Conference on Signals, Systems an Computers . 1999, 2: 1008–1012
6 Quan Z, Cui S, Sayed A H. Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing , 2008, 2(1): 28–40
7 Letaief K B, Zhang W. Cooperative communications for cognitive radio networks. Proceedings of the IEEE , 2009, 97(5): 878–893
doi: 10.1109/JPROC.2009.2015716
8 Sadeghi H, Azmi P. Cyclostationarity-based cooperative spectrum sensing for cognitive radio networks. In: Proceedings of International Symposium on Telecommunications . 2008, 429–434
9 Lunden J, Koivunen V, Huttunen A, Poor H V. Spectrum sensing in cognitive radios based on multiple cyclic frequencies. In: Proceedings of the 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications . 2007, 37–43
10 Lunden J, Koivunen V, Huttunen A, Poor H V. Collaborative cyclostationary spectrum sensing for cognitive radio systems. IEEE Transactions on Signal Processing , 2009, 57(11): 4182–4195
doi: 10.1109/TSP.2009.2025152
11 Li J, Cui W, Jiang H, Wang N. Second-order cyclostationarity analysis of OQAM/OFDM signals. Journal of Rlectronics & Information Technology , 2011, 33(5): 1076–1081
12 Schott J R. Matrix Analysis for Statistics. Wiley-Interscience , 1997
13 Quan Z, Cui S, Sayed A H, Poor H V. Optimal multiband joint detection for spectrum sensing in cognitive radio networks. IEEE Transactions on Signal Processing , 2009, 57(3): 1128–1140
doi: 10.1109/TSP.2008.2008540
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