r
t
⇒Y=
Y
1
T
Y
2
T
r
t
Y
Y
1
T
Y
2
T
(1)
If
s
1
t
s
1
t
is transmitted
Y
1
T=∫-∞∞
s
1
τ
h
1
opt
T-τdτ+
ν
1
T=∫-∞∞
s
1
τ
s
1
*
τdτ+
ν
1
T=
E
s
+
ν
1
T
Y
1
T
τ
s
1
τ
h
1
opt
T
τ
ν
1
T
τ
s
1
τ
s
1
*
τ
ν
1
T
E
s
ν
1
T
(2)
Y
2
T=∫-∞∞
s
1
τ
s
2
*
τdτ+
ν
2
T=
ν
2
T
Y
2
T
τ
s
1
τ
s
2
*
τ
ν
2
T
ν
2
T
(3)
If
s
2
t
s
2
t
is transmitted,
Y
1
T=
ν
1
T
Y
1
T
ν
1
T
and
Y
2
T=
E
s
+
ν
2
T
Y
2
T
E
s
ν
2
T
.
H0
Y=
E
s
0+
ν
1
ν
2
Y
E
s
0
ν
1
ν
2
(4)
H1
Y=0
E
s
+
ν
1
ν
2
Y
0
E
s
ν
1
ν
2
(5)
where
ν
1
ν
1
and
ν
2
ν
2
are independent are Gaussian with zero mean and variance
N
0
2
E
s
N
0
2
E
s
.
The analysis is identical to the
correlator example.
P
e
=Q
E
s
N
0
P
e
Q
E
s
N
0
(6)
Note that the maximum likelihood detector decides based on
comparing
Y
1
Y
1
and
Y
2
Y
2
.
If
Y
1
≥
Y
2
Y
1
Y
2
then
s
1
s
1
was sent; otherwise
s
2
s
2
was transmitted. For a similar analysis for binary antipodal
signals, refer
here. See
Figure 2 or
Figure 3.