CNN-based blind SIR classification framework for STPA-BAA spectrum superposing
In: ICT Express, Jg. 9 (2023), Heft 1, S. 57-62
Online
academicJournal
Zugriff:
Spectrum sharing in the spatial domain among the plurality of wireless communication systems should be addressed due to its exhaustion. We previously conceptualized a spectrum superposing enabled by subcarrier transmission power assignment (STPA) and blind adaptive array (BAA), where co-channel interference can be suppressed even without a priori information of interferer. However, it requires knowledge of input signal-to-interference power ratio (SIR) to realize completely blind operation. This paper proposes a blind SIR estimation framework by convolutional neural network (CNN) using power spectrum images. Simulation verifies the proposed scheme can maximize throughput performance based on SIR classification results with 97% accuracy.
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CNN-based blind SIR classification framework for STPA-BAA spectrum superposing
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Autor/in / Beteiligte Person: | Kobayashi, Hiroaki ; Kojima, Shun ; Maruta, Kazuki ; Sugiyama, Takatoshi ; Ahn, Chang-Jun |
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Zeitschrift: | ICT Express, Jg. 9 (2023), Heft 1, S. 57-62 |
Veröffentlichung: | Elsevier, 2023 |
Medientyp: | academicJournal |
ISSN: | 2405-9595 (print) |
DOI: | 10.1016/j.icte.2021.12.009 |
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