We assume:
Noise power depends on:
From these assumptions:
$P_d \propto SNR = \frac{P_s}{P_n}$
$\frac{SNR}{SNR'} = \frac{P_n'}{P_n}$
In [3]:
BW1 = 1e6
Ns1 = 25e3
BW2 = 2e6
Ns2 = 25e3
BW3 = 10e6
Ns3 =100e3
In [19]:
Pn1 = 10.*log10(BW1)
print "Pn1 =", Pn1, "dB"
In [34]:
Pn2 = 10.*log10(BW2)
print "Pn2 = Pn1 +", Pn2 - Pn1, "dB"
In [35]:
Pn3 = 10.*log10(BW3)
print "Pn3 = Pn1 +", Pn3 - Pn1, "dB"
Reduction in noise power due to averaging.
In [36]:
Pm1 = -10.*log10(Ns1)
print "Pm1 =", Pm1, "dB"
In [37]:
Pm2 = -10.*log10(Ns2)
print "Pm2 = Pm1 +", Pm2 - Pm1, "dB"
In [38]:
Pm3 = -10.*log10(Ns3)
print "Pm2 = Pm1 +", Pm3 - Pm1, "dB"
Combine both effects and compare with experiment results:
In [46]:
P1 = Pn1 + Pm1
print "P1 =", P1, "dB"
Pex1 = -116.1
print "Pex1 =", Pex1, "dB"
In [47]:
P2 = Pn2 + Pm2
print "P2 = P1 + ", P2 - P1, "dB"
Pex2 = -113.5
print "Pex2 = Pex1 +", Pex2 - Pex1, "dB"
In [48]:
P3 = Pn3 + Pm3
print "P3 = P1 + ", P3 - P1, "dB"
Pex3 = -111.6
print "Pex3 = Pex1 +", Pex3 - Pex1, "dB"
In [49]:
BWa = 1.7e6
In [50]:
Pna = 10.*log10(BWa)
In [62]:
Pn1 = 10.*log10(BW1)
print "Pn1 = Pna + ", Pn1 - Pna, "dB"
Pexa1 = -120.5
print "Pex1 = Pexa1 +", Pex1 - Pexa1, "dB"
In [63]:
Pn2 = 10.*log10(BW2)
print "Pn2 = Pna + ", Pn2 - Pna, "dB"
Pexa2 = -119.5
print "Pex2 = Pexa2 +", Pex2 - Pexa2, "dB"
In [64]:
Pn3 = 10.*log10(BW3)
print "Pn3 = Pna + ", Pn3 - Pna, "dB"
Pexa3 = -119.1
print "Pex3 = Pexa3 +", Pex3 - Pexa3, "dB"
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