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2023, Volume 24, Issue 5

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Frontiers of Information Technology & Electronic Engineering >> 2023, Volume 24, Issue 5 doi: 10.1631/FITEE.2200253

DDUC: an erasure-coded system with decoupled data updating and coding

Affiliation(s): College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China; Key Laboratory of Advanced Marine Communication and Information Technology, Ministry of Industry and Information Technology, Harbin Engineering University, Harbin 150001, China; China Coal Technology Engineering Group Chongqing Research Institute, Chongqing 400037, China; State Key Lab of Methane Disaster Monitoring & Emergency Technology, Chongqing 400039, China; less

Received: 2022-06-10 Accepted: 2023-05-31 Available online: 2023-05-31
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Abstract

To improve the accuracy of modulated signal recognition in variable environments and reduce the impact of factors such as lack of prior knowledge on recognition results, researchers have gradually adopted deep learning techniques to replace traditional modulated signal processing techniques. To address the problem of low recognition accuracy of the modulated signal at low signal-to-noise ratios, we have designed a novel network of multi-scale analysis with deep threshold noise elimination to recognize the actually collected modulated signals under a symmetric cross-entropy function of label smoothing. The network consists of a denoising encoder with deep adaptive threshold learning and a decoder with . The two modules are skip-connected to work together to improve the robustness of the overall network. Experimental results show that this method has better recognition accuracy at low signal-to-noise ratios than previous methods. The network demonstrates a flexible self-learning capability for different noise thresholds and the effectiveness of the designed feature fusion module in multi-scale feature acquisition for various modulation types.

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