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Applied Sciences
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Advances in Wireless Networks and Mobile Communication
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Advances in Wireless Networks and Mobile Communication

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 20 January 2026 | Viewed by 408

Special Issue Editor

Prof. Dr. Wei Gong

E-Mail Website
Guest Editor
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230026, China
Interests: wireless networks; mobile communication; distributed computing; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of wireless networks and mobile communication technologies continues to revolutionize connectivity, enabling seamless data transmission, IoT integration, and next-generation applications. This Special Issue aims to explore cutting-edge advancements in 5G/6G networks, AI-driven optimization, edge computing, and ultra-reliable low-latency communications. It also addresses emerging challenges in spectrum efficiency, security, and energy-efficient protocols. By showcasing innovative research and practical solutions, this Issue aims to foster discussions on the future of mobile communication, empowering smarter, faster, and more resilient networks. We invite contributions that push the boundaries of wireless technology, driving progress toward a hyper-connected, intelligent digital ecosystem.

Prof. Dr. Wei Gong
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wireless networks and communication
  • mobile communication systems
  • 5G and 6G technologies
  • edge computing
  • artificial intelligence (AI) and machine learning (ML) for wireless networks

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Published Papers (1 paper)

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Research

21 pages, 1716 KB  
Article
LAI-YOLO: Towards Lightweight and Accurate Insulator Anomaly Detection via Selective Weighted Feature Fusion
by Jianan Qu, Zhiliang Zhu, Ziang Jiang, Congjie Wen and Yijian Weng
Appl. Sci. 2025, 15(19), 10780; https://doi.org/10.3390/app151910780 - 7 Oct 2025
Viewed by 193
Abstract
While insulator integrity is critical for power grid stability, prevailing detection algorithms often rely on computationally intensive models incompatible with resource-constrained edge devices like unmanned aerial vehicles (UAVs). Key limitations—including redundant feature interference, inadequate sensitivity to small targets, rigid fusion weights, and sample [...] Read more.
While insulator integrity is critical for power grid stability, prevailing detection algorithms often rely on computationally intensive models incompatible with resource-constrained edge devices like unmanned aerial vehicles (UAVs). Key limitations—including redundant feature interference, inadequate sensitivity to small targets, rigid fusion weights, and sample imbalance—further restrict practical deployment. To address those problems, this study presents a lightweight insulator anomaly detection algorithm, LAI-YOLO. First, the SqueezeGate-C3k2 (SG-C3k2) module, equipped with an adaptive gating mechanism, is incorporated into the Backbone network to reduce redundant information during feature extraction. Secondly, we propose a High-level Screening–Feature Weighted Feature Pyramid Network (HS-WFPN) to replace FPN+PAN via selective weighted feature fusion, enabling dynamic cross-scale integration and enhanced small-target detection. Then, a reconstructed lightweight detection head coupled with Slide Weighted Focaler Loss (SWFocalerLoss) mitigates performance degradation from sample imbalance. Ultimately, the layer adaptation for the magnitude-based pruning (LAMP) technique slashes computational demands without sacrificing detection prowess. Experimental results on our insulator anomaly dataset demonstrate that the improved model achieves higher efficacy in identifying insulator anomalies, with mAP@0.5 increasing from 88.2% to 91.1%, while model parameters and FLOPs are diminished to 45.7% and 53.9% of the baseline, respectively. This efficiency facilitates the deployment of edge devices and highlights the method’s considerable application potential. Full article
(This article belongs to the Special Issue Advances in Wireless Networks and Mobile Communication)
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