New Challenges in MIMO Communication Systems

Dear Colleagues,

The integration of Multiple-Input Multiple-Output (MIMO) communication systems with machine learning (ML) techniques has opened up new avenues for enhancing the performance, efficiency, and adaptability of wireless networks. This Special Issue aims to explore the synergies between MIMO communication systems and ML, addressing the challenges and opportunities that arise from their integration.

This Special Issue seeks to bring together cutting-edge research at the intersection of MIMO communication systems and machine learning. We look forward to receiving your contributions that investigate novel methodologies, algorithms, and applications leveraging machine learning techniques to address the evolving challenges in MIMO communication systems.

By addressing the convergence of MIMO communication systems and machine learning, this Special Issue aims to foster interdisciplinary research and innovation in wireless communications. We encourage researchers and practitioners to contribute their latest findings and insights to advance the state of the art in this rapidly evolving field.

This Special Issue invites original research contributions, review articles, and case studies that address, but are not limited to, the following topics:

• Joint optimization of MIMO communication and machine learning algorithms.
• Deep learning approaches for MIMO channel estimation and equalization.
• Reinforcement learning for MIMO beamforming and resource allocation.
• Learning-based interference management in MIMO networks.
• Federated learning for distributed MIMO systems.
• Cross-layer optimization integrating machine learning in MIMO communication protocols.
• Transfer learning and domain adaptation for MIMO system deployment.
• Security and robustness considerations in machine learning-enabled MIMO systems.
• Performance evaluation and benchmarking of machine learning algorithms in MIMO communication.
• Real-world applications and case studies of machine learning in MIMO communication systems.
• Machine learning applications.
• Applications of MIMO communication systems.

Submission Guidelines:

Authors are invited to submit original research articles or review papers that address the themes of this Special Issue. All submissions will undergo a rigorous peer-review process to ensure the quality and relevance of the contributions. Manuscripts must follow the formatting guidelines of Applied Sciences and be submitted through the journal's online submission system.

Prof. Dr. Hani Hamdan
Prof. Dr. Huifang Chen
Guest Editors

Dr. Jinan Charafeddine
Guest Editor Assistant

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.

• MIMO communication
• wireless networks
• machine learning