文件名称:How-to-get-SNR-in-cognitive-radio
- 所属分类：
- 3G开发
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- 上传时间：
- 2014-03-08
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- 11kb
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- Joydev******
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monte carlo simulation.
to run the above simulation input" [y1,y2,y3,y4]= ed(0,1,25,2) " in command window.
the "g" in the code above represents the normalisation i.e it represents variance(signal)/variance (noise)
as SNR= power(signal)/power(noise) as the variance of the data is the power.
so i essentially want to "split" the g up. so substitute g= for SNR= power(signal)/power(noise) signal power back into y1 ect.. i.e y1= randn(n,1000000)*sqrt(var(signal))+y0
this is so that i can add the
thank you for any suggestions.
-monte carlo simulation.
to run the above simulation input" [y1,y2,y3,y4]= ed(0,1,25,2) " in command window.
the "g" in the code above represents the normalisation i.e it represents variance(signal)/variance (noise)
as SNR= power(signal)/power(noise) as the variance of the data is the power.
so i essentially want to "split" the g up. so substitute g= for SNR= power(signal)/power(noise) signal power back into y1 ect.. i.e y1= randn(n,1000000)*sqrt(var(signal))+y0
this is so that i can add the
thank you for any suggestions.
to run the above simulation input" [y1,y2,y3,y4]= ed(0,1,25,2) " in command window.
the "g" in the code above represents the normalisation i.e it represents variance(signal)/variance (noise)
as SNR= power(signal)/power(noise) as the variance of the data is the power.
so i essentially want to "split" the g up. so substitute g= for SNR= power(signal)/power(noise) signal power back into y1 ect.. i.e y1= randn(n,1000000)*sqrt(var(signal))+y0
this is so that i can add the
thank you for any suggestions.
-monte carlo simulation.
to run the above simulation input" [y1,y2,y3,y4]= ed(0,1,25,2) " in command window.
the "g" in the code above represents the normalisation i.e it represents variance(signal)/variance (noise)
as SNR= power(signal)/power(noise) as the variance of the data is the power.
so i essentially want to "split" the g up. so substitute g= for SNR= power(signal)/power(noise) signal power back into y1 ect.. i.e y1= randn(n,1000000)*sqrt(var(signal))+y0
this is so that i can add the
thank you for any suggestions.
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How to get SNR in cognitive radio.docx