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Antenna Technology for 5G Communication
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Antenna Technology for 5G 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: 30 June 2025 | Viewed by 577

Special Issue Editors

Dr. Ming-An Chung

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, National Taipei University of Technology, Taipei 10608, Taiwan
Interests: sub-terahertz/millimeter wave/microwave wireless communication integrated circuit chip design and smart antenna system design; artificial intelligence Internet of Things and wearable embedded system design; functional safety analysis of autonomous vehicles; radio waves
Special Issues, Collections and Topics in MDPI journals
Dr. Mengshiuan Pan

E-Mail Website
Guest Editor
Department of Electronic Engineering, National Taipei University of Technology, Taipei 10608, Taiwan
Interests: mobile system protocol design; wearable device applications and IoT; mobile and web application design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite contributions to this Special Issue on "Antenna Technology for 5G Communication". The rapid development of 5G technology has transformed the wireless communication landscape, necessitating advanced antenna solutions that can support higher frequencies, increased data rates, and enhanced connectivity. This Special Issue explores the latest advancements in antenna design, materials, and applications that are pivotal for deploying 5G networks. Research areas may include, but are not limited to, the following:

  1. Novel antenna designs for millimeter-wave frequencies.
  2. MIMO (Multiple Input Multiple Output) antenna systems for improved capacity and efficiency.
  3. Smart antennas and beamforming technologies for dynamic coverage.
  4. Integration of antennas with emerging technologies such as IoT and smart cities.

We look forward to receiving your contributions, which will further enrich the knowledge base in this critical area of research.

Dr. Ming-An Chung
Dr. Mengshiuan Pan
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. 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

  • antenna technology
  • 5G communication
  • millimeter-wave
  • MIMO
  • beamforming
  • IoT
  • smart antennas
  • wireless networks
  • antenna design
  • advanced materials

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Published Papers (1 paper)

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Research

19 pages, 6535 KiB  
Article
Learning Approach for Angle Estimation Based on Characteristics of Phase Drift
by Seoyoung Koh and Jaeho Lee
Appl. Sci. 2025, 15(7), 3708; https://doi.org/10.3390/app15073708 - 28 Mar 2025
Viewed by 291
Abstract
Indoor positioning systems (IPSs) are increasingly vital for various applications on the Internet of Things (IoT), including home automation, navigation in large buildings, AR, and smart city development. These systems rely on techniques such as time of arrival (ToA), angle of arrival (AoA), [...] Read more.
Indoor positioning systems (IPSs) are increasingly vital for various applications on the Internet of Things (IoT), including home automation, navigation in large buildings, AR, and smart city development. These systems rely on techniques such as time of arrival (ToA), angle of arrival (AoA), and received signal strength indicator (RSSI), and Bluetooth low energy (BLE). Despite advancements, challenges such as signal fluctuations, multipath effects, and high infrastructure costs limit the accuracy and adoption of these systems. This paper proposes a deep neural network-based approach to enhance angle estimation by leveraging phase drift values, an underutilized aspect in current models. By employing the phase drift-dependent lightweight angle estimation (PLAE) model, we aim to improve angle prediction accuracy, particularly in complex indoor environments. Experimental results demonstrate that our model achieves higher accuracy compared to traditional methods. The integration of time series data handling capabilities in our approach highlights its potential to provide more reliable indoor positioning solutions. This research contributes to the development of specialized models for precise AoA estimation, addressing the gaps in existing methodologies. Full article
(This article belongs to the Special Issue Antenna Technology for 5G Communication)
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