DocumentCode :
3700419
Title :
A novel cooperative global spectrum sensing algorithm based on variational Bayesian inference
Author :
Ming Wu;Tiecheng Song;Lianfeng Shen;Ziyan Jia;Jing Hu
Author_Institution :
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
This paper proposed an approximate model for the global power spectral density (PSD) of primary users (PUs). Based on the proposed model, a novel cooperative spectrum sensing algorithm was proposed, and its overall flow was also built to obtain global information in the network of PUs. The global information includes locations, occupied frequency bands and transmit powers of the PUs. Then, an estimator of model coefficient vector was designed by utilizing the theory of Variational Bayesian Inference (VBI). Simulation results show that the proposed approximate model has good accuracy, and the corresponding estimation algorithm of model coefficient vector has good convergence and stability. Meanwhile, it is proved that the proposed algorithm has better Mean Square Error (MSE) performance since the sparsity of model coefficient vector is utilized.
Keywords :
"Sensors","Approximation algorithms","Cognitive radio","Bayes methods","Algorithm design and analysis","Inference algorithms","Mobile communication"
Publisher :
ieee
Conference_Titel :
Wireless Communications & Signal Processing (WCSP), 2015 International Conference on
Type :
conf
DOI :
10.1109/WCSP.2015.7341101
Filename :
7341101
Link To Document :
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