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I am doing a project on indoor localisation using fingerprinting. Is it possible to build a system in LabView which can scan the entire spectrum and provide me the RSSI measurements of different types of signals?(say FM, GSM, DVB-T and so on.) In case it has to be done separately, can someone please point me to some resources that would help me to find the RSSIs of say, FM signals? I am new to SDRs and would really appreciate some help. I have used this paper as a reference: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7444902

heisenberg
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1 Answers1

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There can be no general method. RSSI is inherently signal-specific, and hence, for each signal type, you will need a different estimator. An estimator that estimates the received signal strength of FM broadcasts will only see noise in a DVB-T signal at incredibly high noise power with no stable signal at all, whereas a DVB-T RSSI indicator would only see a slowly moving interfere in an FM signal.

I see you're using the tag. That is a very bad thing: In an indoor scenario, fading is extremely important, and your received signal strength allow absolutely no conclusions on the distance to the transmitter. This is pretty much the definition of the indoor channel, where lots and lots of reflections overlap and interefere, and there's not always a direct line of sight between transmitter and receiver.

I'm afraid you still have quite some theory to read up on.

Marcus Müller
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  • Hi, I am sorry for the vague question. I am actually looking to build an indoor positioning system using the method of fingerprinting. This is the reason I need RSSIs. My idea is to utilize the fact that getting RSSIs from more parts of the spectrum(e.g Wi-Fi and FM) would lead to a richer fingerprint, which ultimately leads to higher accuracy. An SDR allows me to reach out to all aspects of the spectrum. Some papers talk about scanning the all the Fm and DVB-T channels and collecting the RSSI records of say x Fm and y DVB-T signals. I am new to SDRs and would really appreciate some help. – heisenberg Jun 11 '16 at 19:40
  • This is what I wished to ask: Is there any way to scan the spectrum and collect RSSIs of different parts of the spectrum( e.g FM, DVB-T, GSM and so on) directly in GNU radio/LabView? I hope that I am able to get my point across. – heisenberg Jun 11 '16 at 19:46
  • Also, can you please point me to some resources on how to build such a signal strength estimator for various signal types in LabView? – heisenberg Jun 11 '16 at 19:52
  • Well, you need to write an estimator for all these classes of signals. That's far from trivial. I don't think, however, that an RSSI would be the necessary thing here – simply taking the signal energy would be an equivalently good way, if you happen to scan enough different emissions. I must admit that I don't see the link between fingerprinting and localization, though! – Marcus Müller Jun 11 '16 at 19:55
  • Fingerprinting is one of the main methods used in indoor localisation. The idea is to go through a "training phase" where we measure the RSSI fingerprints at different points in the reqd area. In the "Validation phase", the fingerprint is again calculated and basic machine learning algorithms are used to calculate the position(by referring the database generated in the training phase). Last qn: Would you be able to give me some insight into what method(just a guess) the authors of the paper(link given in the question) used for the measurement of RSSIs? Really appreciate your help, Thank you! – heisenberg Jun 11 '16 at 20:18
  • This is just in case you think their method is something different from what you suggested. Otherwise, I'll proceed with your method! Thanks again! – heisenberg Jun 11 '16 at 20:26