Reconfigurable Antennas and Fluid Antenna Systems

Description

As wireless systems evolve toward 6G and beyond, there is a growing need for reconfigurable, adaptive, programmable, and intelligent electromagnetic systems that can dynamically respond to changing environments and user demands. Reconfigurable antennas (RA) have been proposed to provide the hardware basis for such adaptability and a variety of novel approaches have been developed including switched, liquid, pixel and moveable antennas. In contrast, fluid antenna systems (FAS), and related techniques, have provided a system-level, hardware-agnostic framework that connects RA to system optimization. As such RA and FAS have emerged as key enabling technologies, offering new degrees of freedom in shaping electromagnetic waves across space, time, frequency, and polarization domains. Correspondingly, reconciling and integrating RA and FAS technologies together, by understanding their individual features, limitations and domains has become important.

This special issue aims to provide a timely and high-impact platform for reporting the latest advances in RA and FAS and fostering interdisciplinary research at the intersection of applied electromagnetics, microwave engineering, and wireless communications. This special issue aims to provide a timely platform for researchers and practitioners to present cutting-edge developments in reconfigurable antennas and fluid antenna systems, fostering interdisciplinary collaboration across electromagnetics, microwave engineering, and communications.

Topics of interest include, but are not limited to:

• Reconfigurable antennas (frequency, pattern, polarization, port, power and bandwidth reconfiguration)
• Fluid antenna systems (FAS) and related techniques: theory, modelling, and experimental validation
• Integration of RA with communication systems, sensing, and signal processing
• Reconfigurable intelligent surfaces (RIS) and programmable meta-surfaces in the context of RA and FAS
• Near-field and Fresnel-region beamforming and focusing in the context of RA and FAS
• AI/ML-enabled antenna design and adaptive control in the context of RA and FAS
• Tuneable materials, RF MEMS, and active components for reconfigurability
• mmWave and THz reconfigurable antenna systems in the context of RA and FAS
• Wireless power transfer and energy focusing using reconfigurable structures
• Channel modelling and system-level analysis for reconfigurable antennas
• Applications in 5G/6G, IoT, sensing, satellite, and HAPS communications in the context of RA and FAS

About JSTEAP:

The IEEE Journal of Selected Topics in Electromagnetics, Antennas and Propagation (JSTEAP) is co-sponsored by the Antennas and Propagation Society (AP-S), Microwave Theory and Technology Society (MTT-S), and the Communications Society (ComSoc). The focus of JSTEAP is on contributions that bridge the gaps between electromagnetics, communications, and microwave technology and manuscripts incorporating at least two of these aspects are particularly encouraged. All types of contributions are welcome including theory, experimental results, designs, applied engineering innovations, surveys, tutorials and reviews. Each issue of JSTEAP is devoted to a specific technical topic and thus provides to JSTEAP readers a collection of up-to-date papers on that topic. These issues are expected to be valuable to the research community and become a source of valuable references.

Open and Transparent Research Exchange

JSTEAP is a fully Open Access journal and is committed to supporting open and transparent research exchange and enabling authors to embrace best practices in data and code sharing. All submitted manuscripts should contain sufficient detail to allow their research contributions and results to be verified and repeated by independent researchers.

For manuscripts with AI-related content, JSTEAP follows IEEE publication policies. In this context, we identify two main categories of submissions; to uphold open and transparent research exchange, the following guidelines apply:

• Manuscripts describing new AI algorithms or substantive methodological advances: Public release of code and training/evaluation datasets is strongly encouraged. If full release is not possible, authors should provide sufficient algorithmic detail and complete training/evaluation protocols, together with access to datasets (public or controlled access), so that independent researchers can reproduce the results.
• Manuscripts applying established AI methods to specific EM/antenna design or propagation modeling problems: These should emphasize verifiable outcomes rather than novelty in the AI methodology. Authors must provide enough detail to enable reproduction of the workflow and results, even if proprietary datasets cannot be released. Acceptable alternatives include: (a) detailed data specifications (e.g., size, sources, preprocessing); (b) full training and inference pipelines (hyperparameters, architectures, loss functions, hardware, compute budget, evaluation metrics); and (c) clear baseline comparisons where feasible.
• Manuscripts with AI contributions outside these categories, or those seeking exceptions to these guidelines, will be considered as long as the principles of open and transparent research exchange — including verification and repeatability of results — are maintained.

Submission Guidelines

Prospective authors should submit their manuscripts following the IEEE JSTEAP guidelines. All submissions must be made through the online JSTEAP Author Portal on ScholarOne. Official templates are available via the IEEE Template Selector for both LaTeX and MS Word. Please click on “IEEE Template Selector” and follow the instructions to access the template you need.

Authors should submit their manuscripts according to the schedule below.

Important Dates