Denoising higher-order moments for blind digital modulation identification in multiple-antenna systems

Kharbech, Sofiane, Simon, Eric Pierre, Belazi, Akram, and Xiang, Wei (2020) Denoising higher-order moments for blind digital modulation identification in multiple-antenna systems. IEEE Wireless Communications Letters, 9 (6). pp. 765-769.

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Abstract

This letter proposes a new technique that substantially improves blind digital modulation identification (DMI) algorithms that are based on higher-order statistics (HOS). The proposed technique takes advantage of noise power estimation to make an offset on higher-order moments (HOM), thus getting an estimate of noise-free HOM. When tested for multiple-antenna systems, the proposed method outperforms other DMI algorithms, in terms of identification accuracy, that are based only on cumulants or do not consider HOM denoising, even for a receiver with impairments. The improvement is achieved with the same order of complexity of the common HOS-based DMI algorithms in the same context.

Item ID: 67184
Item Type: Article (Research - C1)
ISSN: 2162-2345
Keywords: Cognitive radio, denoising features, higher-order statistics, modulation identification, multiple-antenna systems
Copyright Information: © 2020 IEEE
Funders: Beijing Natural Science Foundation (BNSF)
Projects and Grants: BNSF Grant L182032
Date Deposited: 11 May 2021 01:38
Downloads: Total: 3
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