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Measuring Spectrum Similarity in Distributed Radio Monitoring Systems

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 766))

Abstract

The idea of distributed spectrum monitoring with RF front-ends of a few dollars is gaining attention to capture the real-time usage of the wireless spectrum at large geographical scale. Yet the limited hardware of these nodes hinders some of the applications that could be envisioned. In this work, we exploit the fact that, because of its affordable cost, massive deployments of spectrum sensors could be foreseen in the early future, where the radio signal of one wireless transmitter is received by multiple spectrum sensors in range and connected over the public Internet. We envision that nodes in this scenario may collaboratively take decisions about which portion of the spectrum to monitor or not. A key problem for collaborative decision is to identify the conditions where the nodes receive the same spectrum data. We take an initial step in this direction, presenting a collaborative system architecture, and investigating the challenges to correlate pre-processed data in the backend, with key insights in the trade-offs in the system design in terms of network bandwidth and type of over-the-air radio signals. Our results suggest that it is feasible to determinate in the backend if two sensors are reading the same analog/digital signal in the same frequency, only sampling during 200 ms and sending just 1 KB of data per sensor to the backend.

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Notes

  1. 1.

    http://www.rtl-sdr.com/buy-rtl-sdr-dvb-t-dongles/.

  2. 2.

    http://osmocom.org.

  3. 3.

    In details, the RPi is model 3, with 1.2 GHz 64-bit quad-core and 1 GB of RAM.

  4. 4.

    For instance, we have experimentally measured that batches of 100 FFTs of 256 samples/bins each are computed in \({\approx }10\) us using the GPU of the RPi, almost four time less that using the CPU.

  5. 5.

    It can be downloaded at https://github.com/electrosense/es-sensor.

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Acknowledgments

This work has been funded in part by the TIGRE5-CM program (S2013/ICE-2919). We thank the anonymous reviewers for their valuable comments and suggestions.

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Correspondence to Roberto Calvo-Palomino , Domenico Giustiniano or Vincent Lenders .

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Calvo-Palomino, R., Giustiniano, D., Lenders, V. (2017). Measuring Spectrum Similarity in Distributed Radio Monitoring Systems. In: Piva, A., Tinnirello, I., Morosi, S. (eds) Digital Communication. Towards a Smart and Secure Future Internet. TIWDC 2017. Communications in Computer and Information Science, vol 766. Springer, Cham. https://doi.org/10.1007/978-3-319-67639-5_16

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  • DOI: https://doi.org/10.1007/978-3-319-67639-5_16

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-67639-5

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