认知无线网络中基于Cholesky分解的统计协方差频谱检测算法

doi:10.3969/j.issn.1000-436x.2012.z2.015

Abstract

Abstract:

As the blind covariance detection algorithm has the shortcoming that the performance parameters are obtained using non-asymptotic method,a new blind detection algorithm was presented using cholesky factorization.Utilizing random matrix theory,the performance parameters was derived using non-asymptotic method.The proposed method overcomes the noise uncertainty problem and performs well without information about the channel,primary user and noise.Numerical simulation results demonstrate that the performance parameters expressions are correct and the new detector outperforms the other blind covariance detectors.

Key words: covariance matrix, cognitive radio network, wishart distribution, choleskyfactorization, blind detection

Ying-xue LI,Shu-qun SHEN,Lang-tao HU,Qiu-cai WANG. Statistical covariance blind detection algorithm based on cholesky factorization in cognitive radio network[J]. Journal on Communications, 2012, 33(Z2): 118-124.

Figures/Tables 3

References 13

[1]	ATAPATTU S , TELLAMBURA C , JIANG H . Energy detection based cooperative spectrum sensing in cognitive radio networks[J]. IEEE T Wirel Commun, 2011,10(4): 1232-1241.
[2]	ZHAO Y X , SONG M , XIN C S . A weighted cooperative spectrum sensing framework for infrastructure-based cognitive radio networks[J]. Comput Commun, 2011,34(12): 1510-1517.
[3]	ZENG Y H , LIANG Y C . Spectrum-sensing algorithms for cognitive radio based on statistical covariances[J]. Vehicular Technology,IEEE Transactions on, 2009:58(4): 1804-1815.
[4]	RAMIREZ D , VAZQUEZ-VILAR G , LOPEZ-VALCARCE R ,et al. Detection of Rank-P signals in cognitive radio networks with uncalibrated multiple antennas[J]. IEEE T Signal Proces, 2011,59(8): 3764-3774.
[5]	ZENG Y H , LIANG Y C . Maximum-minimum eigenvalue detection for cognitive radio[A]. 2007 IEEE 18th International Symposium on Personal,Indoor and Mobile Radio Communications[C]. Athens,Greece, 2007. 403-407.
[6]	BIANCHI P , NAJIM J , MAIDA M ,et al. Performance analysis of some eigen-based hypothesis tests for collaborative sensing[A]. Proc 2009 IEEE/Sp 15th Workshop on Statistical Signal Processing[C]. Gardiff,UK, 2009. 5-8.
[7]	ZHANG P , QIU R , GUO N . Demonstration of spectrum sensing with blindly learned features[J]. IEEE Commun Lett, 2011,15(5): 548-550.
[8]	BIANCHI P , DEBBAH M , MAIDA M ,et al. Performance of statistical tests for single-source detection using random matrix theory[J]. IEEE Transactions on Information Theory, 2011,57(4): 2400-2419.
[9]	WEI L , TIRKKONEN O . Spectrum sensing in the presence of multiple primary users[J]. IEEE T Commun, 2012,60(5): 1268-1277.
[10]	YANG X , LEI K J , PENG S L ,et al. Blind detection for primary user based on the sample covariance matrix in cognitive radio[J]. IEEE Commun Lett, 2011,15(1): 40-42.
[11]	GUPTA A K , NAGAR D K . Matrix Variate Distributions[M]. London: Vol.3 Chapman＆HallPress, 2000.
[12]	SIMON M K . Probability Distributions Involving Gaussian Random Variables[M]. Berlin: Springer-VerlagPress, 2002.
[13]	ZENG Y H , LIANG Y C . Spectrum-sensing algorithms for cognitive radio based on statistical covariances[J]. IEEE T Veh Technol, 2009,58(4): 1804-1815.

Metrics

Recommended 0

No Suggested Reading articles found!

[1]	Weijie MAI, Weili LIU, Jinghui ZHONG. Self-adaptive differential evolution algorithm based on population state information [J]. Journal on Communications, 2023, 44(6): 34-46.
[2]	Zhengyu ZHU, Yu LIN, Zixuan WANG, Kexian GONG, Pengfei CHEN, Zhongyong WANG, Jing LIANG. Fast blind detection of short-wave frequency hopping signal based on MeanShift [J]. Journal on Communications, 2022, 43(6): 200-210.
[3]	Baoze MA, Guojun LI, Cuiling XIANG, Yang XU. Underdetermined mixing matrix estimation algorithm based on tensor analysis [J]. Journal on Communications, 2022, 43(11): 35-43.
[4]	Yongjun XU,Yang YANG,Qilie LIU,Qianbin CHEN,Jinzhao LIN. Robust power and subcarrier allocation algorithm for cognitive network based on interference efficiency maximization [J]. Journal on Communications, 2020, 41(1): 84-93.
[5]	Jisheng XU,Fanzi ZENG,Kang LI,Yongfeng LI. Performance analysis of two-way relay cooperation underlay cognitive radio networks based on WIPT [J]. Journal on Communications, 2019, 40(2): 129-136.
[6]	Yan LONG,Xiaoqian ZHANG,Xuming FANG,Rong HE. Resource allocation in cognitive radio network with energy harvesting [J]. Journal on Communications, 2018, 39(9): 67-75.
[7]	Jian-ping LIU,Shun-fu JIN,Bao-shuai WANG. Study on optimization strategy for hybrid underlay/overlay spectrum sharing based on queuing model [J]. Journal on Communications, 2017, 38(9): 55-64.
[8]	Xing ZHANG,Ye WANG,Yi YANG,Qin-yu ZHANG. Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm [J]. Journal on Communications, 2017, 38(7): 175-185.
[9]	Xiao-tong MA,Shun-fu JIN,Jian-ping LIU,Zhan-qiang HUO. Study on energy saving strategy and Nash equilibrium of base station in cognitive radio network [J]. Journal on Communications, 2016, 37(7): 172-181.
[10]	Shu-qi LIU,Yi-ming WANG,Cui-mei CUI. Routing approach based on local topology control in cognitive radio networks [J]. Journal on Communications, 2016, 37(5): 106-114.
[11]	Shun-fu JIN,Shi-ying GE,Zhan-qiang HUO. Dynamic spectrum allocation strategy with probabilistic feedback mechanism and performance analysis [J]. Journal on Communications, 2015, 36(7): 10-17.
[12]	Yin MI,Guang-yue LU. Cooperative spectrum sensing algorithm based on limiting eigenvalue distribution [J]. Journal on Communications, 2015, 36(1): 84-89.
[13]	Xin TANG,Zhao-feng MA,Xin-xin NIU,Yi-xian YANG. Blind audio watermarking mechanism based on variational Bayesian learning [J]. Journal on Communications, 2015, 36(1): 121-128.
[14]	Hua JIANG,Li-chuan MA,Ding-yu YAN,Nan PAN. Proactive spectrum handoff in distributed cognitive radio networks [J]. Journal on Communications, 2014, 35(Z2): 196-202.
[15]	. Proactive spectrum handoff in distributed cognitive radio networks [J]. Journal on Communications, 2014, 35(Z2): 27-202.

Statistical covariance blind detection algorithm based on cholesky factorization in cognitive radio network

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 3

References 13

Related Articles 15

Metrics

Recommended 0