Advanced Antennas and Antenna Array Using Machine Learning in Wireless Communication
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".
Deadline for manuscript submissions: 10 October 2024 | Viewed by 226
Special Issue Editor
Special Issue Information
Dear Colleagues,
Future wireless communication technologies require innovative research in ultra-wideband, multi-band, and millimeter-wave applications to satisfy the demands of increasing data rates. Additionally, enhanced bandwidth is needed for future antenna designs, particularly 5G and 6G antennas, to secure low latency data transfer and reduce multipath interferences. All facets of modern civilization are affected by these issues; for example, NextG cellular communications, Internet of Things (IoT) devices, unmanned aerial vehicles (UAVs), missiles, defense systems, and hundreds more cannot act efficiently without extremely high-speed connectivity and multipath interference-canceling capabilities. Therefore, there is a global effort among antenna designers to solve these problems. Researchers are using Machine Learning methods to build antennas more effectively and achieve adaptive band reconfigurability. Autonomous beam scanning and MIMO capability can be enabled via various techniques.
In support of this global initiative, we are announcing a Special Issue on "Advanced Antennas and Antenna Array Using Machine Learning in Wireless Communication". This issue discusses cutting-edge ideas in contemporary millimeter wave, multi-band, ultra-wideband antenna, and array designs using machine learning techniques.
Dr. Elias Alwan
Guest Editor
Manuscript Submission Information
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Keywords
- antennas
- phased array antennas
- computational methods for antenna design
- machine learning in antenna design
- antenna measurement techniques
- MIMO antennas
- antennas for biomedical applications
- artificial intelligence-assisted beamforming techniques
- machine learning antennas
