DocumentCode :
2078945
Title :
Analysis and algorithm for robust adaptive cooperative spectrum-sensing in time-varying environments
Author :
Hongting Zhang ; Hsiao-Chun Wu ; Shih Yu Chang
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Louisiana State Univ., Baton Rouge, LA, USA
fYear :
2013
fDate :
9-13 June 2013
Firstpage :
2617
Lastpage :
2621
Abstract :
The optimal data-fusion rule was first established for multiple-sensor detection systems in 1986. The probability of false alarm and the probability of miss detection required in this data-fusion rule are quite difficult to precisely enumerate in practice. Although the improved data-fusion implementation techniques are available, most existing cooperative spectrum-sensing techniques are still based on the simple energy-detection algorithm, which is prone to failure in many scenarios. In our previous paper, we proposed a novel adaptive cooperative spectrum-sensing scheme based on Jarque-Bera (JB) statistics. However, the commonly-used sample-average estimator for the cumulative weights becomes unreliable in time-varying environments. To overcome this drawback, in this paper, we adopt a temporal discount factor, which is crucial to the probability estimators. New theoretical analysis to justify the advantage of our proposed new estimators over the conventional sample-average estimators and to determine the optimal numerical value of the proposed discount factor is presented. The Monte Carlo simulation results are also provided to demonstrate the superiority of our proposed adaptive cooperative spectrum sensing method in time-varying environments.
Keywords :
Monte Carlo methods; cognitive radio; cooperative communication; radio spectrum management; sensor fusion; signal detection; statistical distributions; Jarque-Bera statistics; Monte Carlo simulation; cumulative weight; data fusion rule; energy detection algorithm; false alarm probability; miss detection probability; multiple sensor detection system; probability estimation; robust adaptive cooperative spectrum sensing; sample average estimator; temporal discount factor; time-varying environment; Cognitive radio; Detectors; Estimation; Polynomials; Probability; Signal to noise ratio; Adaptive cooperative spectrum sensing; JB (Jarque-Bera) statistics; optimal data-fusion rule; temporal discount factor; time-varying environment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2013 IEEE International Conference on
Conference_Location :
Budapest
ISSN :
1550-3607
Type :
conf
DOI :
10.1109/ICC.2013.6654930
Filename :
6654930
Link To Document :
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