{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Calculate path propagation/attenuation according to ITU-R P.452 (16)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## License\n", "\n", "```\n", "Calculate path propagation/attenuation according to ITU-R P.452 (16).\n", "Copyright (C) 2015+ Benjamin Winkel (bwinkel@mpifr.de)\n", "\n", "This program is free software; you can redistribute it and/or\n", "modify it under the terms of the GNU General Public License\n", "as published by the Free Software Foundation; either version 2\n", "of the License, or (at your option) any later version.\n", "\n", "This program is distributed in the hope that it will be useful,\n", "but WITHOUT ANY WARRANTY; without even the implied warranty of\n", "MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n", "GNU General Public License for more details.\n", "\n", "You should have received a copy of the GNU General Public License\n", "along with this program; if not, write to the Free Software\n", "Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.\n", "```" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from astropy import units as u\n", "from pycraf import pathprof\n", "from pycraf import conversions as cnv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Doing generic studies" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For spectrum compatibility studies on the ITU-R level, it is often necessary to do so-called generic studies. These are analyzing compatibility for the smooth-Earth scenario, i.e., assuming the terrain to be completely flat." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Producing the zero-height profile\n", "This is obviously trivial. We just produce a zero-filled numpy array and an appropriate distance vector." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "distances = np.arange(0., 100., 0.05) # 100 km in steps of 50-m\n", "zero_hprof = np.zeros_like(distances)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As for the [terrain-based height profile](https://github.com/bwinkel/pycraf/blob/master/notebooks/03a_path_propagation_basic.ipynb), we first create a `PathProp` instance and call the `loss_complete` function afterwards. Since we use a custom height profile, the Tx/Rx coordinates are not relevant, but since the constructor wants to have a number, we will just feed in dummy values. We will also provide values for $\\Delta N$ and $N_0$, the radiometerological parameters, as the P.452 algorithm needs them." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "lon_t, lon_r = 0 * u.deg, 0 * u.deg\n", "lat_t, lat_r = 50 * u.deg, 50 * u.deg\n", "h_tg, h_rg = 10 * u.m, 50 * u.m # Tx will be within clutter\n", "G_t, G_r = 10. * cnv.dBi, 0. * cnv.dBi\n", "\n", "frequency = 10 * u.GHz\n", "temperature = 293.15 * u.K\n", "pressure = 1013. * u.hPa\n", "\n", "time_percent = 2 * u.percent\n", "DN, N0 = 38. * cnv.dimless / u.km, 324. * cnv.dimless\n", "\n", "zone_t, zone_r = pathprof.CLUTTER.URBAN, pathprof.CLUTTER.UNKNOWN" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ "pprop = pathprof.PathProp(\n", " frequency,\n", " temperature, pressure,\n", " lon_t, lat_t,\n", " lat_t, lat_r,\n", " h_tg, h_rg,\n", " 30. * u.m, # dummy height resolution\n", " time_percent,\n", " zone_t=zone_t, zone_r=zone_r,\n", " delta_N=DN, N0=N0,\n", " hprof_dists=distances * u.km,\n", " hprof_heights=zero_hprof * u.m,\n", " hprof_bearing=90 * u.deg, # have to provide dummy bearings\n", " hprof_backbearing=-90 * u.deg,\n", " )\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The next step is to feed the `PathProp` object into the attenuation function:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "L_bfsg: 153.89 dB - Free-space loss\n", "L_bd: 200.98 dB - Basic transmission loss associated with diffraction\n", "L_bs: 197.07 dB - Tropospheric scatter loss\n", "L_ba: 174.22 dB - Ducting/layer reflection loss\n", "L_b: 174.22 dB - Complete path propagation loss\n", "L_b_corr: 190.32 dB - As L_b but with clutter correction\n", "L: 180.32 dB - As L_b_corr but with gain correction\n" ] } ], "source": [ "tot_loss = pathprof.loss_complete(pprop, G_t, G_r)\n", "(L_bfsg, L_bd, L_bs, L_ba, L_b, L_b_corr, L) = tot_loss\n", "print('L_bfsg: {0.value:5.2f} {0.unit} - Free-space loss'.format(L_bfsg))\n", "print('L_bd: {0.value:5.2f} {0.unit} - Basic transmission loss associated with diffraction'.format(L_bd))\n", "print('L_bs: {0.value:5.2f} {0.unit} - Tropospheric scatter loss'.format(L_bs))\n", "print('L_ba: {0.value:5.2f} {0.unit} - Ducting/layer reflection loss'.format(L_ba))\n", "print('L_b: {0.value:5.2f} {0.unit} - Complete path propagation loss'.format(L_b))\n", "print('L_b_corr: {0.value:5.2f} {0.unit} - As L_b but with clutter correction'.format(L_b_corr))\n", "print('L: {0.value:5.2f} {0.unit} - As L_b_corr but with gain correction'.format(L))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is also interesting to study the attenuation effects as a function of distance:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# have to avoid the first few pixels, as each profile needs to have at\n", "# least 5 or so values for the algorithm to work\n", "\n", "# store attenuations in a numpy record for convenience (without units!)\n", "attens = np.zeros(\n", " distances.shape, \n", " dtype=np.dtype([\n", " ('LOS', 'f8'), ('Diffraction', 'f8'), ('Troposcatter', 'f8'), \n", " ('Ducting', 'f8'), ('Total', 'f8'),\n", " ('Total w. clutter', 'f8'), ('Total w. clutter/gain', 'f8')\n", " ])\n", " )\n", "attens[:5] = 1000. # dB; initialize to huge value \n", "\n", "for idx in range(5, len(distances)):\n", "\n", " pprop = pathprof.PathProp(\n", " frequency,\n", " temperature, pressure,\n", " lon_t, lat_t,\n", " lat_t, lat_r,\n", " h_tg, h_rg,\n", " 30. * u.m, # dummy height resolution\n", " time_percent,\n", " zone_t=zone_t, zone_r=zone_r,\n", " delta_N=DN, N0=N0,\n", " hprof_dists=distances[:idx] * u.km,\n", " hprof_heights=zero_hprof[:idx] * u.m,\n", " hprof_bearing=90 * u.deg, # have to provide dummy bearings\n", " hprof_backbearing=-90 * u.deg,\n", " )\n", " \n", " tot_loss = pathprof.loss_complete(pprop, G_t, G_r)\n", " attens[idx] = u.Quantity(tot_loss).value" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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ioYcesrtK41tbmxXCVq6Elhar7LTT4JZbYP/97a2bDJmGLIpIVAqEw5T5fGz1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\n7Rsb7TXtvoYqYMw3Ej5XFV8blY0svnQxQaFSfElGh8bGRh5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Bnj17qKio8Lby8vJBeblS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vz9739n4sSJTJ8+naFDh97W8xxdZmYmGzduZPXq1axdu5b169dz5op5eu7u7oSFhdGlSxc6d+5M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\nWpq3LlZTDorVlINiNeVg0aSmptKjRw969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"text/plain": [ "<matplotlib.figure.Figure at 0x7fdd67859d68>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.close()\n", "fig = plt.figure(figsize=(14, 8))\n", "ax = fig.add_axes((0.1, 0.1, 0.8, 0.8))\n", "for (name, style) in zip(\n", " attens.dtype.names, \n", " ['b-', 'r-', 'c-', 'm-', 'g-', 'k-.', 'k-']\n", " ):\n", " ax.plot(distances[5:], attens[name][5:], style, label=name, lw=2)\n", "\n", "ax.legend(\n", " *ax.get_legend_handles_labels(), \n", " loc='lower right', fontsize=8, handlelength=3\n", " )\n", "ax.set_xlim((0, 100))\n", "ax.set_ylim((80, 220))\n", "ax.set_xlabel('Distance [km]')\n", "ax.set_ylabel('Path attenuation [dB]')\n", "ax.grid()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "With this, it is easy to see at which distance diffraction kicks in (at about 58 km), because the `L_bd` term shows a sharp bend at this point." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Again, pycraf has a function to do exactly this with less effort and improved computing speed:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "distance = 100 * u.km\n", "hprof_step = 50 * u.m" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "hprof_data = pathprof.height_path_data_generic(\n", " distance, hprof_step, lon_t, lat_t,\n", " zone_t=pathprof.CLUTTER.URBAN, zone_r=pathprof.CLUTTER.SUBURBAN,\n", " )" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [], "source": [ "atten_path, eps_pt_path, eps_pr_path = pathprof.atten_path_fast(\n", " frequency, temperature, pressure,\n", " h_tg, h_rg, time_percent,\n", " hprof_data,\n", " )" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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ezz77DJfL1WcJ+rFqzLTB11+3l6t/8037uLjYXjXx+9+3l7OXMU09ZCIyaoQi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\no62wjef+5zk+O/IZJZYSfub5GfOZ7/P++7mf1cp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SkwaSjWYzAGuld0wSZN544w1KSkq4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\npEksWLCAQ4cO0bNnT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"text/plain": [ "<matplotlib.figure.Figure at 0x7fdd67039160>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.close()\n", "fig = plt.figure(figsize=(14, 8))\n", "ax = fig.add_axes((0.1, 0.1, 0.8, 0.8))\n", "for idx, (name, style) in enumerate(zip(\n", " attens.dtype.names[:-1], \n", " ['b-', 'r-', 'c-', 'm-', 'g-', 'k-.']\n", " )):\n", " ax.plot(\n", " hprof_data['distances'][5:],\n", " atten_path[idx][5:],\n", " style, label=name, lw=2\n", " )\n", "\n", "ax.legend(\n", " *ax.get_legend_handles_labels(), \n", " loc='lower right', fontsize=8, handlelength=3\n", " )\n", "ax.set_xlim((0, 100))\n", "ax.set_ylim((80, 220))\n", "ax.set_xlabel('Distance [km]')\n", "ax.set_ylabel('Path attenuation [dB]')\n", "ax.grid()\n", "plt.show()" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [Root]", "language": "python", "name": "Python [Root]" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 0 }