Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.6
Journals
Electronics
Special Issues
Application of Artificial Intelligence in Wireless Communications
share announcement

Application of Artificial Intelligence in Wireless Communications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 682

Special Issue Editors

Dr. Haolin Tang

E-Mail Website
Guest Editor
School of Engineering and Computing, Fairfield University, Fairfield, CT 06824, USA
Interests: wireless communications; NextG; machine learning
Dr. Yanxiao Zhao

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA
Interests: wireless communication and networking; machine learning; cybersecurity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of wireless communication technologies has significantly transformed how information is transmitted and processed. With the advent of 5G and the emergence of 6G, the demand for high-speed, low-latency, and ultra-reliable communication has intensified. Artificial Intelligence (AI) has emerged as a powerful tool to address these challenges, offering innovative solutions for network optimization, resource allocation, signal processing, and security enhancement.

This Special Issue aims to explore AI's latest advancements and applications in wireless communications, highlighting cutting-edge research that integrates machine learning, deep learning, and reinforcement learning into wireless communication systems. Original research articles and reviews are welcome. Topics of interest include but are not limited to, AI-driven spectrum management, intelligent multiple access techniques, AI-enhanced massive MIMO, energy-efficient wireless networks, and AI-enabled security frameworks.

By bringing together contributions from researchers and practitioners, this Special Issue seeks to highlight innovative AI applications that push the boundaries of wireless communication technologies. The insights gained from these studies will have profound implications for developing next-generation wireless networks, including 6G, the Internet of Things (IoT), and edge computing.

Dr. Haolin Tang
Dr. Yanxiao Zhao
Guest Editors

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. Electronics 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
  • wireless networking
  • MIMO
  • communication system security
  • deep learning
  • artificial intelligence

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 25849 KiB  
Article
A Hybrid Approach to Semantic Digital Speech: Enabling Gradual Transition in Practical Communication Systems
by Münif Zeybek, Bilge Kartal Çetin and Erkan Zeki Engin
Electronics 2025, 14(6), 1130; https://doi.org/10.3390/electronics14061130 - 13 Mar 2025
Viewed by 489
Abstract
Recent advances in deep learning have fostered a transition from the traditional, bit-centric paradigm of Shannon’s information theory to a semantic-oriented approach, emphasizing the transmission of meaningful information rather than mere data fidelity. However, black-box AI-based semantic communication lacks structured discretization and remains [...] Read more.
Recent advances in deep learning have fostered a transition from the traditional, bit-centric paradigm of Shannon’s information theory to a semantic-oriented approach, emphasizing the transmission of meaningful information rather than mere data fidelity. However, black-box AI-based semantic communication lacks structured discretization and remains dependent on analog modulation, which presents deployment challenges. This paper presents a new semantic-aware digital speech communication system, named Hybrid-DeepSCS, a stepping stone between traditional and fully end-to-end semantic communication. Our system comprises the following parts: a semantic encoder for extracting and compressing structured features, a standard transmitter for digital modulation including source and channel encoding, a standard receiver for recovering the bitstream, and a semantic decoder for expanding the features and reconstructing speech. By adding semantic encoding to a standard digital transmission, our system works with existing communication networks while exploring the potential of deep learning for feature representation and reconstruction. This hybrid method allows for gradual implementation, making it more practical for real-world uses like low-bandwidth speech, robust voice transmission over wireless networks, and AI-assisted speech on edge devices. The system’s compatibility with conventional digital infrastructure positions it as a viable solution for IoT deployments, where seamless integration with legacy systems and energy-efficient processing are critical. Furthermore, our approach addresses IoT-specific challenges such as bandwidth constraints in industrial sensor networks and latency-sensitive voice interactions in smart environments. We test the system under various channel conditions using Signal-to-Distortion Ratio (SDR), PESQ, and STOI metrics. The results show that our system delivers robust and clear speech, connecting traditional wireless systems with the future of AI-driven communication. The framework’s adaptability to edge computing architectures further underscores its relevance for IoT platforms, enabling efficient semantic processing in resource-constrained environments. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in Wireless Communications)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop