Add PAPRStats module

1 files changed, 146 insertions, 0 deletions

diff --git a/src/PAPRStats.cpp b/src/PAPRStats.cpp
new file mode 100644
index 0000000..bf6acc4
--- /dev/null
+++ b/src/PAPRStats.cpp
@@ -0,0 +1,146 @@
+/*
+   Copyright (C) 2005, 2006, 2007, 2008, 2009, 2010, 2011 Her Majesty
+   the Queen in Right of Canada (Communications Research Center Canada)
+
+   Copyright (C) 2017
+   Matthias P. Braendli, matthias.braendli@mpb.li
+
+    http://opendigitalradio.org
+ */
+/*
+   This file is part of ODR-DabMod.
+
+   ODR-DabMod is free software: you can redistribute it and/or modify
+   it under the terms of the GNU General Public License as
+   published by the Free Software Foundation, either version 3 of the
+   License, or (at your option) any later version.
+
+   ODR-DabMod is distributed in the hope that it will be useful,
+   but WITHOUT ANY WARRANTY; without even the implied warranty of
+   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+   GNU General Public License for more details.
+
+   You should have received a copy of the GNU General Public License
+   along with ODR-DabMod.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+#include "PAPRStats.h"
+#include <numeric>
+#include <cmath>
+#if defined(TEST)
+/* compile with g++ -std=c++11 -Wall -DTEST PAPRStats.cpp -o paprtest */
+#  include <iostream>
+#endif
+
+
+PAPRStats::PAPRStats(size_t num_blocks_to_accumulate) :
+    m_num_blocks_to_accumulate(num_blocks_to_accumulate)
+{
+}
+
+void PAPRStats::process_block(const complexf* data, size_t data_len)
+{
+    double norm_peak = 0;
+    double rms2 = 0;
+
+    for (size_t i = 0; i < data_len; i++) {
+        const double x_norm = std::norm(data[i]);
+
+        if (x_norm > norm_peak) {
+            norm_peak = x_norm;
+        }
+
+        rms2 += x_norm;
+    }
+
+    rms2 /= data_len;
+
+#if defined(TEST)
+    std::cerr << "Accumulating peak " << norm_peak <<
+        " rms2 " << rms2 << std::endl;
+#endif
+
+    m_squared_peaks.push_back(norm_peak);
+    m_squared_mean.push_back(rms2);
+
+    if (m_squared_mean.size() > m_num_blocks_to_accumulate) {
+        m_squared_mean.pop_front();
+        m_squared_peaks.pop_front();
+    }
+}
+
+double PAPRStats::calculate_papr()
+{
+    if (m_squared_mean.size() < m_num_blocks_to_accumulate) {
+        return 0;
+    }
+
+    if (m_squared_mean.size() != m_squared_peaks.size()) {
+        throw std::logic_error("Invalid PAPR measurement sizes");
+    }
+
+    double peak = 0;
+    double rms2 = 0;
+    for (size_t i = 0; i < m_squared_peaks.size(); i++) {
+        if (m_squared_peaks[i] > peak) {
+            peak = m_squared_peaks[i];
+        }
+
+        rms2 += m_squared_mean[i];
+    }
+
+    // This assumes all blocks given to process have the same length
+    rms2 /= m_squared_peaks.size();
+
+#if defined(TEST)
+    std::cerr << "Calculate peak " << peak <<
+        " rms2 " << rms2 << std::endl;
+#endif
+
+    return 10.0 * std::log10(peak / rms2);
+}
+
+#if defined(TEST)
+/* Test python code:
+import numpy as np
+vec = 0.5 * np.exp(np.complex(0, 0.3) * np.arange(40))
+vec[26] = 10.0 * vec[26]
+rms = np.mean(vec * np.conj(vec)).real
+peak = np.amax(vec * np.conj(vec)).real
+print("rms {}".format(rms))
+print("peak {}".format(peak))
+print(10. * np.log10(peak / rms))
+*/
+int main(int argc, char **argv)
+{
+    using namespace std;
+    vector<complexf> vec(40);
+
+    for (size_t i = 0; i < vec.size(); i++) {
+        vec[i] = polar(0.5, 0.3 * i);
+        if (i == 26) {
+            vec[i] *= 10;
+        }
+        cout << " " << vec[i];
+    }
+    cout << endl;
+
+    PAPRStats stats(4);
+
+    for (size_t i = 0; i < 3; i++) {
+        stats.process_block(vec.data(), vec.size());
+    }
+
+    const auto papr0 = stats.calculate_papr();
+    if (papr0 != 0) {
+        cerr << "Expected 0, got " << papr0 << endl;
+    }
+
+    stats.process_block(vec.data(), vec.size());
+
+    const auto papr1 = stats.calculate_papr();
+    cout << "PAPR = " << papr1 << " dB" << endl;
+
+}
+
+#endif