Cheaper SDRs use a low-quality crystal oscillator which usually has a large offset from the ideal frequency. Furthermore, that frequency offset will change as the dongle warms up or as the ambient temperature changes. The result is that any signals received will not be at the correct frequency, and they would drift as the temperature changes. CalibrateSDR can be used with almost any SDR to determine the frequency offset. <\/p>\n\n\n\n
The work on GSM<\/strong> (2G) has been done by Jayaraj J<\/a>, mentored by Andreas Hornig, as part of Google Summer of Code 2021<\/a>, the working directory for the same can be found at Github<\/a>.<\/p>\n\n\n\n GSM uses time division to share a frequency channel among users. Each frequency is divided into blocks of time that are known as time-slots. 8 time-slots are numbers TS0 \u2013 TS7. Each time slot lasts about 576.9\u00a0 \u03bcs. The bit rate is 270.833 kb\/s, a total of 156.25 bits can be transmitted in each slot.<\/p>\n\n\n\n Each slot allocates 8.25 of its \u201ebits time\u201c as guard-time, split between the beginning and the end of each time slot. Data transmitted within each time slot is called a burst. There are several types of bursts.<\/p>\n\n\n\n Frequency correction<\/em> burst is a burst of a pure frequency tone at 1\/4th the bitrate of GSM or (1625000 \/ 6) \/ 4 = 67708.3 Hz. By searching a channel for this pure tone, we can determine its clock offset by determining how far away from 67708.3Hz the received frequency is.<\/p>\n\n\n\n After cloning the repo locally, run the setup to install the requirements using the command:\u00a0 After that, to run the visualization plots, run:<\/p>\n\n\n\n First, we will get the plot of the\u00a0average power spectrum<\/strong>\u00a0plot. Play with the code to increase the N value, and you can see the sharpness of the line.<\/p>\n\n\n\n Further plots generated includes TDMA frames, the position of FCCH bursts visualisation as given below.<\/p>\n\n\n\n We can see the pure tone FCCH bursts are occurring at specific intervals and can be visualized as small blue dots at a range of 0.25 from the centre.<\/p>\n\n\n\n Thus implementation of a filter bank and calculating the positions of these FCCH bursts will give us the offset frequency since we know these FCCH bursts occur at a distance of 67708.3 Hz from the frequency centre.<\/p>\n\n\n\n Test files for GSM, recorded by Andreas can be found here<\/a>.<\/p>\n\n\n\n usage: cali.py [-h] [-f F] [-m {dab,dvbt,gsm}] [-s {rtlsdr}] [-c C] [-rs RS] [-rg RG] [-rd RD] [-nsec NSEC] [-gr] [-v] [-fc FC]<\/p>\n\n\n\n optional arguments: The ARFCN Bands include: GSM_850, GSM_R_900, GSM_900, GSM_E_900, DCS_1800, PCS_1900.<\/em> For more information about the arfcn, checkout here<\/a>.<\/p>\n\n\n\n Example usage:<\/p>\n\n\n\n The above parameters can be changed according to user needs. -rs can be specified with sample rate. The exact sample rate will be shown with the result. Make sure the SDR is connected when running the code with The expected output would look like this:<\/p>\n\n\n\n The Offset calculated from the frequency drift between fcch positions can be precisely derived and can be used to correct the oscillator.<\/p>\n\n\n\n References:<\/strong><\/p>\n\n\n\n Find out the project updates in my branch and do give a star for the project in AerospaceResearch org:<\/p>\n\n\n\n https:\/\/github.com\/aerospaceresearch\/CalibrateSDR\/tree\/jyrj_dev<\/a><\/p>\n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" Overview CalibrateSDR\u00a0developed by\u00a0Andreas Hornig,\u00a0is a tool developed to determine the frequency drift of Software Defined Radios precisely using sync pulses of various Signal Standards. \u00a0 Cheaper SDRs use a low-quality crystal oscillator which usually has a large offset from the ideal frequency. Furthermore, that frequency offset will change as the dongle warms up or as … \u201e[GSoC2021] CalibrateSDR GSM Support\u201c<\/span> weiterlesen<\/a><\/p>\n","protected":false},"author":29,"featured_media":2270,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[25,33,16,30],"_links":{"self":[{"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/posts\/2349"}],"collection":[{"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/users\/29"}],"replies":[{"embeddable":true,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2349"}],"version-history":[{"count":13,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/posts\/2349\/revisions"}],"predecessor-version":[{"id":2400,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/posts\/2349\/revisions\/2400"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=\/wp\/v2\/media\/2270"}],"wp:attachment":[{"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2349"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2349"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aerospaceresearch.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2349"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"\/](\"https:\/\/aerospaceresearch.net\/wp-content\/uploads\/2021\/07\/CalibrateSDRAerospaceResearch-Jayaraj-J.png\")
Project Description<\/h2>\n\n\n\n
How is it working?<\/strong><\/h5>\n\n\n\n
To test with the IQ_file.wave<\/strong>:<\/h5>\n\n\n\n
python setup.py install<\/code><\/p>\n\n\n\npython cali.py -m gsm -f <location of wav file> -rs <sampling rate> -fc <frequency center><\/code><\/pre>\n\n\n\n![\"\"\/](\"https:\/\/lh5.googleusercontent.com\/VBlZ-uUXlQqOHUFL9uqWbNHA5wCvyUBu2O0nGc6fZ_byErJgcFYBHyWKKSmYNgO4tTQJRWhB9tueG5mvtg-mIo8DKOPHyxr6YOk3gFkY6CevULNOjH8DBryXNgnu4TTn9p7OQ2VN\")
![\"Screenshot-spectrogram_hann-Zoomed.png\"](\"https:\/\/github.com\/aerospaceresearch\/CalibrateSDR\/blob\/jyrj_dev\/tests\/gsm\/Screenshot-spectrogram_hann-Zoomed.png?raw=true\")
<\/figure>\n\n\n\n![\"\"](\"https:\/\/aerospaceresearch.net\/wp-content\/uploads\/2021\/08\/Figure_1.png\")
Usage<\/strong><\/h2>\n\n\n\n
~$ python cali.py -h<\/code><\/li><\/ul>\n\n\n\n-h<\/code>, –help show this help message and exit-f<\/code> F select path to input file-m<\/code> {dab,dvbt,gsm} select mode-s<\/code> {rtlsdr} scan with rtlsdr-c<\/code> C scan by „all“ channels, by channel number „0,1,\u2026n“ or by block name-rs<\/code> RS file\/scan sample rate-rg<\/code> RG scan with gain-rd<\/code> RD scan with the device-nsec<\/code> NSEC scan for n-seconds-gr<\/code>, –graph activate graphs-v<\/code>, –verbose an optional argument-fc<\/code> FC frequency centreSetup the environment, make sure the requirements are installed (preferably in a virtualenv). Use the setup.py to install necessary requirements.<\/p>\n\n\n\n~$ python cali.py -m gsm -f <location of wav file> -rs <sampling rate> -fc <frequency center><\/code><\/pre>\n\n\n\n~$ python cali.py -m gsm -s rtlsdr -c 900<\/code><\/pre>\n\n\n\n-s rtlsdr<\/code> argument. Specify the -fc<\/code> frequency argument, if the scan is to be done with a single frequency. <\/p>\n\n\n\n{'f': None, 'm': 'gsm', 's': 'rtlsdr', 'c': '900', 'rs': 2048000, 'rg': 20, 'rd': 0, 'nsec': 10, 'graph': False, 'verbose': False, 'fc': None}\nlet's find your SDR's oscillator precision\nscanning\u2026\nstarting mode: gsm\nFound Rafael Micro R820T\/2 tuner\nExact sample rate is: 270833.002142 Hz\nScanning all GSM frequencies in band: GSM_900\nOffset Frequency: 31031.66666666667\nOffset in PPM: 33.179448397684716<\/pre>\n\n\n\nPotential further improvements:<\/strong><\/h5>\n\n\n\n