Fluid Antenna Systems (FAS) introduce dynamically reconfigurable radiating apertures that transform every major branch of signal processing---channel estimation, DOA estimation, beamforming, sparse recovery, statistical detection, and machine learning---from inference under a fixed observation model into joint sensing-and-inference design problems. This Special Issue of IEEE Signal Processing Magazine invites tutorial-style overview articles, comprehensive surveys, and original contributions with broad appeal that address the signal processing challenges and opportunities introduced by FAS. Topics include channel modeling, performance bounds, channel estimation and tracking, beamforming and precoding, array signal processing, sparse recovery, statistical detection, machine learning, ISAC, RIS-aided FAS, near-field processing, hardware-aware design, and standardization. Submitted manuscripts must make clear contributions to signal processing theory, algorithms, or methodology. Papers that focus primarily on communication system-level performance evaluation (e.g., throughput, outage probability) without substantial signal processing innovation are outside the scope of this special issue. 

Manuscripts should conform to the standard format as indicated in the Manuscript Submission Guidelines on the IEEE Signal Processing Magazine website . All manuscripts must be submitted through the Author Portal. Select the "Signal Processing for Fluid Antenna Systems: Foundations, Algorithms, and Emerging Applications" topic from the drop-down menu.

Important Dates:

• 1 August 2026 --- White Paper Due
• 1 September 2026 --- Invitation Notification
• 15 November 2026 --- Full-Length Manuscripts Due
• 15 February 2027 --- First Review to Authors
• 15 April 2027 --- Revision Due
• 15 June 2027 --- Final Decision
• 1 August 2027 --- Final Package Due
• December 2027 --- Publication

Guest Editors:

• Tuo Wu (Lead GE)
  South China University of Technology, Guangdong, China
  E-mail: wutuo@scut.edu.cn
• Maged Elkashlan
  Queen Mary University of London, London E1 4NS, U.K.
  E-mail: maged.elkashlan@qmul.ac.uk
• Dominic K. C. Ho
  University of Missouri, Columbia, MO 65211, USA
  E-mail: hod@missouri.edu
• Hing Cheung So
  City University of Hong Kong, Hong Kong SAR, China
  E-mail: hcso@ee.cityu.edu.hk
• Lifeng Mai
  Electric Power Research Institute, China Southern Power Grid, Guangzhou, China
  E-mail: mailf@csg.cn