Digital Signal Processing Reference
In-Depth Information
v R ( t )
=
s ( t ) c ( t )
+
n ( t )
2 P S d ( t ) c ( t ) cos
(7.2)
v R ( t )
=
ω c t
+
n ( t )
After multiplying the received signal by PN chip code c(t) we get,
2 P S d ( t ) c 2 ( t ) cos
v m ( t )
=
ω c t
+
n ( t ) c ( t )
2 P S d ( t ) cos
(7.3)
v m ( t )
=
ω c t
+
n ( t ) c ( t )
The 2nd term of the Eq. ( 7.3 ) indicates the noise is chopped, i.e. (1) noise is spread
whereas wanted data is de-spread and hence (2) power spectral density lowers as
shown in the Fig. 7.7 .
Next, v m (t) is again passed through another multiplier, integrator, i.e. BPSK
detector. The probed signals are as follows.
= P S (2 cos 2
v o ( t )
ω c t ) d ( t )
+
n ( t ) c ( t ) cos
ω c t
(7.4)
The signal v 0 (t)isthensampledatt
=
kT B to get the final output v L (t).
T B
v L ( t )
=
v o ( t ) dt ; k
=
1
0
(7.5)
T B
P S (2 cos 2
ω c t dt
v L ( t )
=
ω c t ) d ( t )
+
n ( t ) c ( t ) cos
=
d ( t )
0
By this way the data signal d(t) has been correctly detected at the end output.
7.4.3 Probability of Error Calculation
From the discussions of Chaps 3 and 6 , it has been shown that, the probability of
error of BPSK for matched filter reception without employing spread spectrum is
2 erfc E S
1 / 2
1
P e =
(7.6)
η
η 2 is the two sided power spectral density
where, E S is the symbol energy,
(variance) of the noise.
To consider the case of direct sequence spread spectrum incorporated with BPSK
(Eq. 7.2 ), within bit interval 0
t
T B , the transmitted signal is
s t ( t )
=
d ( t ) g ( t ) c ( t ) cos 2
π
f c t ;0
t
T B
(7.7)
 
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