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Selecting a Receiver for Wideband Spectrum Sensing in Cognitive Radio Systems Based on an Assessment of the Signal Environment Complexity

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2021, ruSMART 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 13158))

Abstract

A matrix receiver and a sub-Nyquist receiver are shown to provide the processing of the largest number of time-superimposed pulses. In practice, still, the number of pulses’ overlaps depends on the signal environment complexity. Besides, from the point of view of the wideband analyzer, random factors determine this environment. Therefore, to select the receiver type suitable for the developed wideband analyzer (WBA), a quantitative indicator of the signal environment complexity is required. In this paper, the probability of overlap not less than M pulses is proposed as such an indicator. The expressions obtained for calculating this probability allowed to plot the probability of overlapping in time of M and more pulses against the number of radio emission sources at different duty-off factors of the pulse sequences emitted the sources. To ease the attribution of obtained probabilities to actual operating conditions of the WBA, the paper provides the numbers of radars of various purposes which can form a signal environment with given complexity. The paper also gives recommendations on selecting an optimal receiver for the developed wideband analyzer considering implementation complexity and the desired ratio overlapped pulses processing efficiency. The latter is understood to be a ration of successfully processed overlapped pulses under predicted analyzer’s operational conditions characterized by types and numbers of radio emission sources. To summarize, the presented results make it possible to select a receiver for the wideband spectrum sensing depending on the potential complexity of the signal environment.

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Authors and Affiliations

  1. Saint Petersburg Electrotechnical University “LETI”, St. Petersburg, Russia

    Alexey S. Podstrigaev & Andrey V. Smolyakov

  2. Zhukovsky-Gagarin Air Force Academy, Voronezh, Russia

    Vladimir P. Likhachev

  3. Saint Petersburg State University of Aerospace Instrumentation, Saint Petersburg, Russia

    Sergei E. Efimov

  4. Peter the Great Saint Petersburg Polytechnic University, St. Petersburg, 195251, Russia

    Vadim V. Davydov

  5. The Bonch-Bruevich Saint - Petersburg State University of Telecommunications, Saint Petersburg, 193232, Russia

    Vadim V. Davydov

Authors
  1. Alexey S. Podstrigaev
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  2. Andrey V. Smolyakov
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  3. Vladimir P. Likhachev
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  4. Sergei E. Efimov
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  5. Vadim V. Davydov
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Correspondence to Alexey S. Podstrigaev .

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  1. Tampere University, Tampere, Finland

    Yevgeni Koucheryavy

  2. FRUCT Oy, Helsinki, Finland

    Sergey Balandin

  3. Tampere University, Tampere, Finland

    Sergey Andreev

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Podstrigaev, A.S., Smolyakov, A.V., Likhachev, V.P., Efimov, S.E., Davydov, V.V. (2022). Selecting a Receiver for Wideband Spectrum Sensing in Cognitive Radio Systems Based on an Assessment of the Signal Environment Complexity. In: Koucheryavy, Y., Balandin, S., Andreev, S. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2021 2021. Lecture Notes in Computer Science(), vol 13158. Springer, Cham. https://doi.org/10.1007/978-3-030-97777-1_30

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  • DOI: https://doi.org/10.1007/978-3-030-97777-1_30

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