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Afficher davantage de fils d'Ariane
Renaud Gonce
Master Thesis Codes
Validations
c6689fb7
Valider
c6689fb7
rédigé
5 years ago
par
Renaud Gonce
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c6689fb7
%% GFSK Fixed-point implementation
%% Transmission
%%% Transmission/modulation parameters
% fixed-point precision
prec_op_TX
=
32
;
% precision to be used for the operations performed on the considered signal
prec_cst
=
8
;
% precision for the constants
f_c
=
2.45e09
;
% Carrier frequency
r_symb
=
1e06
;
% Symbol rate
Ts
=
1
/
r_symb
;
% Symbol period
m
=
0.5
;
% Modulation index
BTb
=
0.5
;
% Bandwidth - Symbol perdiod product
N_symb
=
1e04
;
% Number of symbols used for the simulation
reso
=
8
;
% Resolution factor (number of samples by symbol period)
dfppm
=
20
;
%%% For BER vs Eb/N0 plot and noise variance (N0) generation
Nsnr
=
16
;
% Number of different values for the plot
Eb_N0_dB
=
linspace
(
0
,
Nsnr
-
1
,
Nsnr
);
Eb_N0
=
10.
^
(
Eb_N0_dB
/
10
);
Eb
=
1
;
N0
=
Eb
.
/
Eb_N0
;
%%% Generation of the preamble
preamble
=
fi
([
1
;
-
1
;
1
;
-
1
;
1
;
-
1
;
1
;
-
1
],
1
,
prec_cst
,
prec_cst
-
1
);
Lpreamble
=
length
(
preamble
);
N_symb
=
N_symb
-
Lpreamble
;
Lnoisestart
=
92
;
N_symb
=
N_symb
-
Lnoisestart
;
%%% Generation of the sequence of symbols (I)
bits
=
fi
(
round
(
rand
(
N_symb
,
1
)),
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
16
-
1
,
'ProductWordLength'
,
16
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
16
-
1
,
'SumWordLength'
,
16
);
I0
=
bits
-
0.5
;
I1
=
I0
*
2
;
I1
(
1
)
=
fi
(
1
,
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
16
-
1
,
'ProductWordLength'
,
16
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
16
-
1
,
'SumWordLength'
,
16
);
I1
(
2
)
=
fi
(
1
,
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
16
-
1
,
'ProductWordLength'
,
16
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
16
-
1
,
'SumWordLength'
,
16
);
I
=
fi
([
preamble
;
I1
],
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
16
-
1
,
'ProductWordLength'
,
16
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
16
-
1
,
'SumWordLength'
,
16
);
LI
=
length
(
I
);
%%% Gaussian pulse-shape filter (g) generation
N_Ts
=
3
;
% Number of symbol periods for the filter support
time
=
-
N_Ts
/
2
*
Ts
:
Ts
/
reso
:
N_Ts
/
2
*
Ts
;
% Filter support
Tb
=
Ts
;
% Here, we will always have Tb=Ts
K
=
sqrt
(
log
(
2
));
% Parameter for the filter amplitude
g
=
g_GMSK
(
time
,
K
,
Tb
,
BTb
);
% Filter generation, using my function "g_GMSK"
Lg
=
length
(
g
);
% g_GMSK can be precomputed and tabled since it is constant, so it does not
% have to be calculated in fixed-point, only the final values are
% converted.
gfi
=
fi
(
g
,
1
,
16
,
16
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
16
-
1
,
'ProductWordLength'
,
16
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
16
-
1
,
'SumWordLength'
,
16
);
%%% Convolution (convo) between the symbol sequence and the Gaussian filter
tmin
=
(
reso
*
(
LI
-
1
)
+
Lg
+
1
)/
2
-
(
reso
*
LI
)/
2
;
tmax
=
(
reso
*
(
LI
-
1
)
+
Lg
+
1
)/
2
+
(
reso
*
LI
)/
2
;
Iup
=
upsample
(
I
,
reso
);
convfiIupgfi
=
convfi
(
Iup
,
gfi
'
,
16
,
prec_op_TX
);
convofi
=
convfiIupgfi
(
tmin
:
tmax
);
Lconvo
=
length
(
convofi
);
%%% Integration (integfi) of the convolution (trapezium method)
% First, we divide everything by 256 as it is the max value the integral
% can output considering a packet of +-300 bits. This way, saturation is
% avoided.
convofi
=
bitsra
(
convofi
,
8
);
integfi
=
fi
(
zeros
(
Lconvo
-
1
,
1
),
1
,
32
,
32
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_TX
-
1
,
'ProductWordLength'
,
prec_op_TX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_TX
-
1
,
'SumWordLength'
,
prec_op_TX
);
integfi
(
1
)
=
bitsra
(
convofi
(
1
)
+
convofi
(
2
),
log2
(
2
*
reso
));
% Division is performed via arithmetic shift right
for
i
=
2
:
Lconvo
-
1
integfi
(
i
)
=
integfi
(
i
-
1
)
+
bitsra
(
convofi
(
i
)
+
convofi
(
i
+
1
),
log2
(
2
*
reso
));
end
% To avoid saturation resulting from multiplication by pi/2, the signal
% should be divided by 2.
integfi
=
bitsra
(
integfi
,
1
);
%%% Phase (phi) generation
fipi_2
=
fi
(
pi
/
2
,
1
,
prec_cst
,
prec_cst
-
2
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_TX
-
1
,
'ProductWordLength'
,
prec_op_TX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_TX
-
1
,
'SumWordLength'
,
prec_op_TX
);
phifi
=
fipi_2
*
integfi
;
Lphifi
=
length
(
phifi
);
%%% Transmitted signal (s) generation
s
=
exp
(
1
j
*
double
(
phifi
)
*
2
^
9
);
Ls
=
length
(
s
);
%% Reception
% Fixed-point precision
prec_op_RX
=
16
;
precRX
=
16
;
% Table of values for the CFO correction:
ak
=
[
-
0.894221291841193
;
...
-
0.823171345055248
;
...
-
0.624515667660133
;
...
-
0.335010157734548
;
...
0
;
...
0.335010157734548
;
...
0.624515667660133
;
...
0.823171345055248
;
...
0.894221291841193
;
...
0.823171345055248
;
...
0.624515667660133
;
...
0.335010157734548
;
...
0
;
...
-
0.335010157734548
;
...
-
0.624515667660133
;
...
-
0.823171345055248
];
sinak
=
sin
(
ak
);
cosak
=
cos
(
ak
);
sinakfi
=
fi
(
sinak
,
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
cosakfi
=
fi
(
cosak
,
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
pow_cosak2pifi_m1
=
fi
(
1.
/(
cosak
*
2
*
pi
),
1
,
prec_cst
,
prec_cst
-
1
);
BERcorrfi
=
zeros
(
Nsnr
,
1
);
BERfi
=
zeros
(
Nsnr
,
1
);
df_hatfi
=
zeros
(
Nsnr
,
1
);
ind_trig
=
zeros
(
Nsnr
,
1
);
SFindi
=
zeros
(
Nsnr
,
1
);
% Loop for each different value of the noise variance
% for i = 1:Nsnr
SNR
=
13
;
for
i
=
SNR
+
1
%%% AWGN (n) generation
% noise can remain in floating-point, it doesn't matter as it will be
% converted as soon as it will be added to the signal.
N
=
N0
(
i
)
*
reso
;
n
=
awgn
(
Lnoisestart
*
reso
+
Ls
,
1
,
N
);
%%% Received signal (r) generation
r
=
[
zeros
(
Lnoisestart
*
reso
,
1
)
;
s
]
+
n
;
Lr
=
length
(
r
);
%%% CFO
df
=
dfppm
/
1e06
*
f_c
;
time
=
(
1
/(
r_symb
*
reso
)
:
1
/(
r_symb
*
reso
)
:
(
Lr
)/(
r_symb
*
reso
))
'
;
rcfo
=
exp
(
1
j
*
2
*
pi
*
df
*
time
)
.*
r
;
rcfofi0
=
fi
(
rcfo
,
1
,
precRX
,
precRX
-
4
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
% /!\ abs(rcfof) can go up to 13 (result from 100000 iterations
% with 300 bits and SNR=13dB) => a normalization by 16 should be
% performed.
rcfofi
=
fi
(
bitsra
(
rcfofi0
,
4
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
Lrcfo
=
length
(
rcfo
);
%%% Filtering of the received CFO'ed signal
% This is done in digital, so from now on signals must be in
% fixed-point. But the filter can be precomputed, so only its final
% coefficient values have to be converted.
% Moreover, as the filter coefficients are <= 1, there is no need
% for normalization. But one is done nonetheless as rcfo needs one.
fcut
=
0.6e06
;
Nper
=
12
;
h0
=
LPF
(
'Hamming'
,
fcut
,
reso
,
Nper
);
h0fi
=
fi
(
h0
,
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
rconvfih0fi0
=
convfi
(
rcfofi
,
h0fi
'
,
prec_op_RX
,
prec_op_RX
);
rconvfih0fi
=
rconvfih0fi0
(
1
+
Nper
/
2
*
reso
:
end
-
Nper
/
2
*
reso
);
rficfof
=
rconvfih0fi
;
%%% Preamble detection
% Hermitian product
OSR
=
reso
;
Hprodfi0
=
rficfof
(
1
+
OSR
:
end
)
.*
conj
(
rficfof
(
1
:
end
-
OSR
));
% IIR filter
IIRb
=
1
;
IIRa
=
zeros
(
OSR
+
1
,
1
);
IIRa
(
1
)
=
1
;
IIRa
(
OSR
+
1
)
=
0.875
;
impu
=
eye
(
500
,
1
);
impuresp
=
filter
(
IIRb
,
IIRa
,
impu
);
% impuresp can be precomputed and tabled, so only the final values
% need to be converted into fixed-point.
impurespfi
=
fi
(
impuresp
,
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
% /!\ abs(IIRHprod) can go up to 350 (result from 100000 iterations
% with 300 bits and SNR=13dB) => a normalization by 512 should be
% performed, normalization of Hprodfi. But it is already 16*16 =
% 256 times smaller due to the previous normalization, so it needs
% an additional normalization factor of only 2 to reach 512!
Hprodfi
=
fi
(
bitsra
(
Hprodfi0
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
IIRHprodfi0
=
convfi
(
Hprodfi
,
impurespfi
,
precRX
,
prec_op_RX
);
IIRHprodfi
=
IIRHprodfi0
(
1
:
end
-
(
length
(
impu
)
-
1
));
absIIRHprodfi
=
abs
(
IIRHprodfi
);
LabsIIRHprodfi
=
length
(
absIIRHprodfi
);
% Search for preamble
if
(
SNR
==
13
)
thresh
=
37.5
;
elseif
(
SNR
==
14
)
thresh
=
32.5
;
end
% Due to the normalization, the comparison must be done wrt a
% threshold that has undergone the same normalization.
threshfi
=
fi
(
thresh
/
2
^
(
4
+
4
+
1
),
1
,
prec_cst
,
prec_cst
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_cst
-
1
,
'ProductWordLength'
,
prec_cst
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_cst
-
1
,
'SumWordLength'
,
prec_cst
);
p
=
1
;
booly
=
false
;
while
(
booly
==
false
)
if
(
absIIRHprodfi
(
p
)
>
threshfi
)
booly
=
true
;
elseif
(
p
>=
LabsIIRHprodfi
)
booly
=
true
;
fprintf
(
'Error, after 1000 iterations, there is still no value that has reached the threshold!'
);
else
p
=
p
+
1
;
end
end
ind_trig
(
i
)
=
p
;
%%% Symbol timing recovery
Noffset
=
5
;
offset
=
Noffset
*
reso
;
maxxtemp
=
absIIRHprodfi
(
ind_trig
(
i
)
+
offset
);
indtemp
=
ind_trig
(
i
)
+
offset
;
kk
=
1
;
while
(
kk
<
1
*
reso
)
if
(
absIIRHprodfi
(
ind_trig
(
i
)
+
offset
+
kk
)
>
maxxtemp
)
maxxtemp
=
absIIRHprodfi
(
ind_trig
(
i
)
+
offset
+
kk
);
indtemp
=
ind_trig
(
i
)
+
offset
+
kk
;
end
kk
=
kk
+
1
;
end
SFindi
(
i
)
=
indtemp
;
%%% CFO correction
df_hat_temp1
=
0
;
Nperiod
=
6
;
b
=
1
;
counter
=
1
;
afikind
=
zeros
(
Nperiod
*
reso
,
1
);
symbrfi
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
symbrfiold
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
hermifi_unnorm
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
hermifi
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
demodsymbrfirfiold
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
dkfi
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
dfhfi
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
dfh1fi0
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
dfh1fi
=
fi
(
zeros
(
Nperiod
*
reso
,
1
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
while
(
b
<=
Nperiod
*
reso
)
symbrfi
(
b
)
=
rficfof
(
b
+
ind_trig
(
i
)
+
reso
-
1
);
symbrfiold
(
b
)
=
rficfof
(
b
+
ind_trig
(
i
)
+
reso
-
1
-
reso
);
hermifi_unnorm
(
b
)
=
symbrfi
(
b
)
*
conj
(
symbrfiold
(
b
));
% The division for the normalization is somehow problematic,
% as I don't know how to handle this in Matlab, I "cheat" by
% using a double value for the divider.
hermifi
(
b
)
=
hermifi_unnorm
(
b
)/
double
(
abs
(
hermifi_unnorm
(
b
)));
demodsymbrfirfiold
(
b
)
=
imag
(
hermifi
(
b
));
dkfi0
=
demodsymbrfirfiold
(
b
);
% Must be divided by 2 to avoid saturation when subtracting it
% with sinakfik
dkfi
(
b
)
=
bitsra
(
dkfi0
,
1
);
% Simulated the index to fetch the values from the LUTs.
afikind
(
b
)
=
mod
(
b
,
2
*
reso
);
if
(
afikind
(
b
)
==
0
)
afikind
(
b
)
=
2
*
reso
;
end
sinakfik0
=
sinakfi
(
afikind
(
b
));
% Must be divided by 2 to avoid saturation when subtracting it
% from dkfi
sinakfik
=
bitsra
(
sinakfik0
,
1
);
dfh1fi0
(
b
)
=
(
dkfi
(
b
)
-
sinakfik
)
*
pow_cosak2pifi_m1
(
afikind
(
b
));
% Here, I accumulate Nperiod*reso (48) values, so I have to
% normalize by this value beforehand (48->64).
dfh1fi
(
b
)
=
bitsra
(
dfh1fi0
(
b
),
6
);
df_hat_temp1
=
df_hat_temp1
+
dfh1fi
(
b
);
dfhfi
(
b
)
=
df_hat_temp1
/
counter
;
counter
=
counter
+
1
;
b
=
b
+
1
;
end
df_hatfi
(
i
)
=
dfhfi
(
end
);
normfact
=
2
^
7
/
Tb
;
% Correction is done in RF, and the denormalization is performed at
% the same time using the factor normfact.
rcorr
=
exp
(
-
1
j
*
2
*
pi
*
(
double
(
df_hatfi
(
i
))
*
normfact
)
*
time
((
Lnoisestart
+
Lpreamble
)
*
reso
+
1
:
end
))
.*
rcfo
((
Lnoisestart
+
Lpreamble
)
*
reso
+
1
:
end
);
rcorrfi0
=
fi
(
rcorr
,
1
,
precRX
);
% Looks like convfi(rcorrfi,h0fi) can go up to 10, so it seems
% appropriate to normalize by 16.
rcorrfi
=
fi
(
bitsra
(
rcorrfi0
,
4
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
rcorrficonvfih0fi0
=
convfi
(
rcorrfi
,
h0fi
'
,
precRX
,
prec_op_RX
);
rcorrficonvfih0fi
=
rcorrficonvfih0fi0
(
1
+
Nper
/
2
*
reso
:
end
-
Nper
/
2
*
reso
);
rcorrfif
=
rcorrficonvfih0fi
;
%%% Filtering of the received signal (for the CFO-free case)
rfi0
=
fi
(
r
,
1
,
precRX
);
% Looks like convfi(rfi,h0fi) can go up to 12, so it seems appropriate
% to normalize by 16.
rfi
=
fi
(
bitsra
(
rfi0
,
4
),
1
,
precRX
,
precRX
-
1
,
'ProductMode'
,
'SpecifyPrecision'
,
'ProductFractionLength'
,
prec_op_RX
-
1
,
'ProductWordLength'
,
prec_op_RX
,
'SumMode'
,
'SpecifyPrecision'
,
'SumFractionLength'
,
prec_op_RX
-
1
,
'SumWordLength'
,
prec_op_RX
);
rficonvfih0fi0
=
convfi
(
rfi
,
h0fi
'
,
precRX
,
prec_op_RX
);
rficonvfih0fi
=
rficonvfih0fi0
(
1
+
Nper
/
2
*
reso
:
end
-
Nper
/
2
*
reso
);
rfif
=
rficonvfih0fi
;
%%% Demodulation
indidown
=
mod
(
SFindi
(
i
)
+
2
,
reso
);
if
(
indidown
==
0
)
indidown
=
reso
;
end
rcorrfifdown
=
downsample
(
rcorrfif
(
indidown
:
end
),
reso
/
2
);
Lrcorrfifdown
=
length
(
rcorrfifdown
);
if
(
mod
(
Lrcorrfifdown
,
2
)
==
0
)
demodficorr
=
imag
(
rcorrfifdown
(
2
:
2
:
end
)
.*
conj
(
rcorrfifdown
(
1
:
2
:
end
-
1
)));
else
demodficorr
=
imag
(
rcorrfifdown
(
2
:
2
:
end
-
1
)
.*
conj
(
rcorrfifdown
(
1
:
2
:
end
-
2
)));
end
Ldemodficorr
=
length
(
demodficorr
);
rfifdown
=
downsample
(
rfif
(
indidown
:
end
),
reso
/
2
);
Lrfifdown
=
length
(
rfifdown
);
if
(
mod
(
Lrfifdown
,
2
)
==
0
)
demodfi
=
imag
(
rfifdown
(
2
:
2
:
end
)
.*
conj
(
rfifdown
(
1
:
2
:
end
-
1
)));
else
demodfi
=
imag
(
rfifdown
(
2
:
2
:
end
-
1
)
.*
conj
(
rfifdown
(
1
:
2
:
end
-
2
)));
end
demodfi
=
demodfi
(
1
+
Lpreamble
+
Lnoisestart
:
end
);
Ldemodfi
=
length
(
demodfi
);
%%% Decision
Icorrfi_hat
=
sign
(
demodficorr
);
BERcorrfi
(
i
)
=
sum
(
sign
(
I
(
1
+
Lpreamble
:
Lpreamble
+
Ldemodficorr
))
~=
Icorrfi_hat
)/
N_symb
;
Ifi_hat
=
sign
(
demodfi
);
BERfi
(
i
)
=
sum
(
sign
(
I
(
1
+
Lpreamble
:
Lpreamble
+
Ldemodfi
))
~=
Ifi_hat
)/
N_symb
;
end
% BER vs Eb/N0 plot
figure
;
semilogy
(
Eb_N0_dB
,
BERcorrfi
,
'xg'
,
'LineWidth'
,
1.5
,
'MarkerSize'
,
8
);
hold
on
;
semilogy
(
Eb_N0_dB
,
BERfi
,
'xk'
,
'LineWidth'
,
1.5
,
'MarkerSize'
,
8
);
axis
([
0
Nsnr
10
/
N_symb
1
]);
grid
;
title
(
strcat
(
'BER -- df = '
,
num2str
(
df
))
);
xlabel
(
'E_{b}/N_{0} [dB]'
);
ylabel
(
'BER'
);
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