基于因子图的分布式变分稀疏贝叶斯压缩感知

doi:10.3969/j.issn.1000-436x.2014.01.016

Abstract

Abstract:

A distributed variational sparse Bayesian compressed spectrum sensing algorithm based on factor graph was proposed,which decomposed the global spectrum sensing problem into local problem based on factor and variation.Belief propagation was used for the statistical inference of the spectrum occupancy,to implement the “soft fusion”.The temporal and spatial correlation information providing two-dimensional redundancies was exchanged among cooperative cognitive users to improve the detection performance under low SNR.Meanwhile,the algorithm prunes the divergence of hyper-parameters and the corresponding basis functions for reducing the load of communication.The simulation results show that this method can effectively achieve performance of spectrum sensing under a low sampling rate and the low SNR.

Key words: cognitive radio, spectrum sensing, factor graph, variational sparse Bayesian learning

Cui-tao ZHU,Fan YANG,Han-xin WANG,Zhong-jie LI. Distributed variational sparse Bayesian compressed sensing based on factor graphs[J]. Journal on Communications, 2014, 35(1): 140-147.

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References 14

[1]	CHAKRAVARHY V , LI X , WU Z ,et al. Novel overlay/underlay cognitive radio waveforms using sd-smse framework to enhance spectrum efficiency-partⅡ:analysis in fading channels[J]. IEEE Transactions on Communications, 2010,58(6): 1868-1876.
[2]	ZHI T . Compressed wideband sensing in cooperative cognitive radio networks[A]. The IEEE Global Communications Conference[C]. New Orleans,LA,USA, 2008.
[3]	曾凡仔, 刘洁, 李仁发等. 基于一致优化的分布式宽带合作频谱感知算法[J]. 通信学报, 2011,32(9): 147-152. ZENG F Z , LIU J , LI R F ,et al. Distributed cooperative spectrum sensing based on consensus optimization[J]. Journal on Communications, 2011,32(9): 147-152.
[4]	WANG Z X , YANG T . Markov compressive sensing in cognitive radio using factor graph[J]. Information and Electronic Engineering, 2012,10(4): 396-400.
[5]	XUE L , STEVEN H , ZHU H ,et al. Bayesian compressed sensing based dynamic joint spectrum sensing and primary user localization for dynamic spectrum access[A]. The IEEE Global Communications Conference[C]. Houston,Texas,USA, 2011.
[6]	朱翠涛, 杨凡 . 基于变分稀疏贝叶斯学习的频谱检测方法[J]. 中南民族大学学报(自然科学版), 2013,32(1): 65-69. ZHU C T，YANG F . Spectrum detection based on variational sparse Bayesian learning[J]. Journal of South-Central University for Nationalities(Nat Sci Edition), 2013,32(1): 65-69.
[7]	KSCHISCHANG F R , FREY B J . Factor graphs and the sum-product algorithm[J]. IEEE Transactions on Information Theory, 2001,47(2): 498-519.
[8]	BISHOP C M , TIPPING M E . Variational relevance vector machines[A]. Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence[C]. San Francisco,CA,USA, 2000. 46-53.
[9]	RAPPPOT T S . Wireless Communications:Principles and Practice[M]. Prentice Hall PTR, 2002.
[10]	HONG S . Direct spectrum sensing form compressed measurements[A]. The IEEE Conference for Military Communications[C]. California,USA, 2011. 1187-1192.
[11]	BAZERQUE J A , GIANNAKIS G.B . Distributed spectrum sensing for cognitive radio networks by exploiting sparsity[J]. IEEE Transactions on Signal Process, 2010,58(3): 1847-1862.
[12]	JI S , XUE Y , CARIN L . Bayesian compressive sensing[J]. IEEE Transactions on Signal Process, 2008,56(6): 2346-2356.
[13]	BISHOP C M . Pattern Recognition and Machine Learning (Information Science and Statistics)[M]. Singapore: SpringerPress, 2006.
[14]	BUCHGRABER T , SHUTIN D . Sparse Bayesian consensus based distributed field estimation[A]. The 5th International Conference on Signal Processing and Communication Systems[C]. Honolulu,USA, 2011.

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β	θ_th	CVSBL算法	DVSBL算法
1×10⁴	1×10⁴	?19.12	?18.92
1×10⁶	1×10⁴	?19.12	?20.03
1×10⁸	1×10⁴	?19.12	?20.05
1×10⁶	1×10⁶	?19.20	?20.31
1×10⁸	1×10⁶	?19.20	?20.34

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Distributed variational sparse Bayesian compressed sensing based on factor graphs

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