A Discrete-Event Network Simulator
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dsss-error-rate-model.cc
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1/*
2 * Copyright (c) 2010 The Boeing Company
3 *
4 * SPDX-License-Identifier: GPL-2.0-only
5 *
6 * Author: Gary Pei <guangyu.pei@boeing.com>
7 */
8
10
11#include "ns3/log.h"
12
13#include <cmath>
14
15#ifdef HAVE_GSL
16#include <gsl/gsl_cdf.h>
17#include <gsl/gsl_integration.h>
18#include <gsl/gsl_math.h>
19#include <gsl/gsl_sf_bessel.h>
20#endif
21
22namespace ns3
23{
24
25NS_LOG_COMPONENT_DEFINE("DsssErrorRateModel");
26
27#ifndef HAVE_GSL
28const double DsssErrorRateModel::WLAN_SIR_PERFECT = 10.0;
30#endif
31
32double
34{
36 return ((M_SQRT2 + 1.0) / std::sqrt(8.0 * M_PI * M_SQRT2)) * (1.0 / std::sqrt(x)) *
37 std::exp(-(2.0 - M_SQRT2) * x);
38}
39
40double
42{
44 double EbN0 = sinr * 22000000.0 / 1000000.0; // 1 bit per symbol with 1 MSPS
45 double ber = 0.5 * std::exp(-EbN0);
46 return std::pow((1.0 - ber), static_cast<double>(nbits));
47}
48
49double
51{
53 double EbN0 = sinr * 22000000.0 / 1000000.0 / 2.0; // 2 bits per symbol, 1 MSPS
54 double ber = DqpskFunction(EbN0);
55 return std::pow((1.0 - ber), static_cast<double>(nbits));
56}
57
58double
60{
62#ifdef HAVE_GSL
63 // symbol error probability
64 double EbN0 = sinr * 22000000.0 / 1375000.0 / 4.0;
65 double sep = SymbolErrorProb16Cck(4.0 * EbN0 / 2.0);
66 return std::min(1.0, std::pow(1.0 - sep, nbits / 4.0));
67#else
68 NS_LOG_WARN("Running a 802.11b CCK Matlab model less accurate than GSL model");
69 // The Matlab model
70 double ber;
71 if (sinr > WLAN_SIR_PERFECT)
72 {
73 ber = 0.0;
74 }
75 else if (sinr < WLAN_SIR_IMPOSSIBLE)
76 {
77 ber = 0.5;
78 }
79 else
80 {
81 // fitprops.coeff from Matlab berfit
82 double a1 = 5.3681634344056195e-001;
83 double a2 = 3.3092430025608586e-003;
84 double a3 = 4.1654372361004000e-001;
85 double a4 = 1.0288981434358866e+000;
86 ber = a1 * std::exp(-std::pow((sinr - a2) / a3, a4));
87 }
88 return std::min(1.0, std::pow((1.0 - ber), static_cast<double>(nbits)));
89#endif
90}
91
92double
94{
96#ifdef HAVE_GSL
97 NS_LOG_DEBUG("GSL enabled ");
98 // symbol error probability
99 double EbN0 = sinr * 22000000.0 / 1375000.0 / 8.0;
100 double sep = SymbolErrorProb256Cck(8.0 * EbN0 / 2.0);
101 return std::min(1.0, std::pow(1.0 - sep, nbits / 8.0));
102#else
103 NS_LOG_WARN("Running a 802.11b CCK Matlab model less accurate than GSL model");
104 // The Matlab model
105 double ber;
106 if (sinr > WLAN_SIR_PERFECT)
107 {
108 ber = 0.0;
109 }
110 else if (sinr < WLAN_SIR_IMPOSSIBLE)
111 {
112 ber = 0.5;
113 }
114 else
115 {
116 // fitprops.coeff from Matlab berfit
117 double a1 = 7.9056742265333456e-003;
118 double a2 = -1.8397449399176360e-001;
119 double a3 = 1.0740689468707241e+000;
120 double a4 = 1.0523316904502553e+000;
121 double a5 = 3.0552298746496687e-001;
122 double a6 = 2.2032715128698435e+000;
123 ber = (a1 * sinr * sinr + a2 * sinr + a3) /
124 (sinr * sinr * sinr + a4 * sinr * sinr + a5 * sinr + a6);
125 }
126 return std::min(1.0, std::pow((1.0 - ber), static_cast<double>(nbits)));
127#endif
128}
129
130#ifdef HAVE_GSL
131double
132IntegralFunction(double x, void* params)
133{
134 double beta = ((FunctionParameters*)params)->beta;
135 double n = ((FunctionParameters*)params)->n;
136 double IntegralFunction = std::pow(2 * gsl_cdf_ugaussian_P(x + beta) - 1, n - 1) *
137 std::exp(-x * x / 2.0) / std::sqrt(2.0 * M_PI);
138 return IntegralFunction;
139}
140
141double
142DsssErrorRateModel::SymbolErrorProb16Cck(double e2)
143{
144 double sep;
145 double error;
146
147 FunctionParameters params;
148 params.beta = std::sqrt(2.0 * e2);
149 params.n = 8.0;
150
151 gsl_integration_workspace* w = gsl_integration_workspace_alloc(1000);
152
153 gsl_function F;
154 F.function = &IntegralFunction;
155 F.params = &params;
156
157 gsl_integration_qagiu(&F, -params.beta, 0, 1e-7, 1000, w, &sep, &error);
158 gsl_integration_workspace_free(w);
159 if (error == 0.0)
160 {
161 sep = 1.0;
162 }
163
164 return 1.0 - sep;
165}
166
167double
168DsssErrorRateModel::SymbolErrorProb256Cck(double e1)
169{
170 return 1.0 - std::pow(1.0 - SymbolErrorProb16Cck(e1 / 2.0), 2.0);
171}
172
173#endif
174
175} // namespace ns3
static double GetDsssDqpskSuccessRate(double sinr, uint64_t nbits)
Return the chunk success rate of the differential encoded QPSK.
static const double WLAN_SIR_PERFECT
WLAN perfect.
static double GetDsssDbpskSuccessRate(double sinr, uint64_t nbits)
Return the chunk success rate of the differential BPSK.
static double GetDsssDqpskCck5_5SuccessRate(double sinr, uint64_t nbits)
Return the chunk success rate of the differential encoded QPSK for 5.5Mbps data rate.
static double GetDsssDqpskCck11SuccessRate(double sinr, uint64_t nbits)
Return the chunk success rate of the differential encoded QPSK for 11Mbps data rate.
static const double WLAN_SIR_IMPOSSIBLE
WLAN impossible.
static double DqpskFunction(double x)
A function DQPSK.
#define NS_LOG_COMPONENT_DEFINE(name)
Define a Log component with a specific name.
Definition log.h:191
#define NS_LOG_DEBUG(msg)
Use NS_LOG to output a message of level LOG_DEBUG.
Definition log.h:257
#define NS_LOG_FUNCTION_NOARGS()
Output the name of the function.
#define NS_LOG_WARN(msg)
Use NS_LOG to output a message of level LOG_WARN.
Definition log.h:250
Every class exported by the ns3 library is enclosed in the ns3 namespace.