Files uploaded

.gitignore

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+input_files/*
+Python_code/phase_processing/*
+Python_code/processed_phase/*
+Python_code/doppler_traces*/*
+Python_code/plots/*
+Python_code/outputs/*
+Python_code/logs/*
+Python_code/cache_files/*
+Python_code/networks/*
+Python_code/evaluations/*
+*.asv
+*00001
+*.index
+*.h5
+.idea/*
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+*.out
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/

Python_code/CSI_doppler_computation.py

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+
+"""
+    Copyright (C) 2023 Francesca Meneghello
+    contact: [email protected]
+    This program 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.
+    This program 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 this program.  If not, see <https://www.gnu.org/licenses/>.
+"""
+
+import argparse
+import numpy as np
+import scipy.io as sio
+import math as mt
+from scipy.fftpack import fft
+from scipy.fftpack import fftshift
+from scipy.signal.windows import hann
+import pickle
+import os
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('dir', help='Directory of data')
+    parser.add_argument('subdirs', help='Sub-directories')
+    parser.add_argument('dir_doppler', help='Directory to save the Doppler data')
+    parser.add_argument('start', help='Start processing', type=int)
+    parser.add_argument('end', help='End processing (samples from the end)', type=int)
+    parser.add_argument('sample_length', help='Number of packet in a sample', type=int)
+    parser.add_argument('sliding', help='Number of packet for sliding operations', type=int)
+    parser.add_argument('noise_level', help='Level for the noise to be removed', type=float)
+    parser.add_argument('--bandwidth', help='Bandwidth in [MHz] to select the subcarriers, can be 20, 40, 80 '
+                                            '(default 80)', default=80, required=False, type=int)
+    parser.add_argument('--sub_band', help='Sub_band idx in [1, 2, 3, 4] for 20 MHz, [1, 2] for 40 MHz '
+                                           '(default 1)', default=1, required=False, type=int)
+    parser.add_argument('--sub_sampling', help='Sampling in [1, 2, 3, 4, 5]'
+                                               '(default 1)', default=1, required=False, type=int)
+    args = parser.parse_args()
+
+    sub_sampling = args.sub_sampling
+    num_symbols = args.sample_length
+    # num_symbols = mt.ceil(num_symbols / sub_sampling)
+
+    middle = int(mt.floor(num_symbols / 2))
+
+    Tc = 7.5e-3
+    fc = 5785e6
+    v_light = 3e8
+
+    sliding = args.sliding
+    noise_lev = args.noise_level
+    bandwidth = args.bandwidth
+    sub_band = args.sub_band
+
+    list_subdir = args.subdirs
+
+    for subdir in list_subdir.split(','):
+        path_doppler = args.dir_doppler + subdir
+        if not os.path.exists(path_doppler):
+            os.mkdir(path_doppler)
+
+        exp_dir = args.dir + subdir + '/'
+
+        names = []
+        all_files = os.listdir(exp_dir)
+        for i in range(len(all_files)):
+            names.append(all_files[i][:-4])
+
+        for name in names:
+            path_doppler_name = path_doppler + '/' + name + '_bandw' + str(bandwidth) + \
+                                '_RU' + str(sub_band) + \
+                                '_sampling' + str(sub_sampling) + '.txt'
+            if os.path.exists(path_doppler_name):
+                continue
+
+            print(path_doppler_name)
+            name_file = exp_dir + name + '.mat'
+            mdic = sio.loadmat(name_file)
+            csi_matrix_processed = mdic['csi_matrix_processed']
+
+            csi_matrix_processed = csi_matrix_processed[args.start:-args.end, :, :]
+
+            csi_matrix_processed[:, :, 0] = csi_matrix_processed[:, :, 0] / np.mean(csi_matrix_processed[:, :, 0],
+                                                                                    axis=1,  keepdims=True)
+
+            csi_matrix_complete = csi_matrix_processed[:, :, 0]*np.exp(1j*csi_matrix_processed[:, :, 1])
+
+            if sub_sampling != 1:
+                csi_matrix_complete = csi_matrix_complete[0:-1:sub_sampling, :]
+
+            if bandwidth == 40:
+                if sub_band == 1:
+                    selected_subcarriers_idxs = np.arange(-500, -17, 1) + 500
+                elif sub_band == 2:
+                    selected_subcarriers_idxs = np.arange(17, 500, 1) + 500
+                num_selected_subcarriers = selected_subcarriers_idxs.shape[0]
+                csi_matrix_complete = csi_matrix_complete[:, selected_subcarriers_idxs]
+            elif bandwidth == 20:
+                if sub_band == 1:
+                    selected_subcarriers_idxs = np.arange(-500, -259, 1) + 500
+                elif sub_band == 2:
+                    selected_subcarriers_idxs = np.arange(-258, -17, 1) + 500
+                elif sub_band == 3:
+                    selected_subcarriers_idxs = np.arange(17, 258, 1) + 500
+                elif sub_band == 4:
+                    selected_subcarriers_idxs = np.arange(259, 500, 1) + 500
+                num_selected_subcarriers = selected_subcarriers_idxs.shape[0]
+                csi_matrix_complete = csi_matrix_complete[:, selected_subcarriers_idxs]
+
+            csi_d_profile_list = []
+            for i in range(0, csi_matrix_complete.shape[0]-num_symbols, sliding):
+                csi_matrix_cut = csi_matrix_complete[i:i+num_symbols, :]
+                csi_matrix_cut = np.nan_to_num(csi_matrix_cut)
+
+                hann_window = np.expand_dims(hann(num_symbols), axis=-1)
+                csi_matrix_wind = np.multiply(csi_matrix_cut, hann_window)
+                csi_doppler_prof = fft(csi_matrix_wind, n=100, axis=0)
+                csi_doppler_prof = fftshift(csi_doppler_prof, axes=0)
+
+                csi_d_map = np.abs(csi_doppler_prof * np.conj(csi_doppler_prof))
+                csi_d_map = np.sum(csi_d_map, axis=1)
+                csi_d_profile_list.append(csi_d_map)
+            csi_d_profile_array = np.asarray(csi_d_profile_list)
+            csi_d_profile_array_max = np.max(csi_d_profile_array, axis=1, keepdims=True)
+            csi_d_profile_array = csi_d_profile_array/csi_d_profile_array_max
+            csi_d_profile_array[csi_d_profile_array < mt.pow(10, noise_lev)] = mt.pow(10, noise_lev)
+
+            with open(path_doppler_name, "wb") as fp:  # Pickling
+                pickle.dump(csi_d_profile_array, fp)