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Reasoning-Enhanced Neural Networks in Wireless Signal Processing

   
   

As wireless environments grow increasingly dynamic and complex, traditional signal processing methods are reaching their limits. In this session, experts explore the urgent need for smarter wireless signal processing, emphasizing the limitations of conventional neural networks, which—while effective at detection and estimation—struggle with generalization, interpretability, and adaptability.  Reasoning-Enhanced Neural Networks, a new paradigm that fuses deep learning with reasoning capabilities, is explored as well as hybrid models that can capture causal relationships, enforce logical constraints, and adapt to dynamic environments, enabling a shift from reactive to proactive signal processing. 

Featured speakers discuss cutting-edge reasoning techniques—such as graph neural networks (GNNs) for relational reasoning, reinforcement learning (RL) for temporal reasoning, neural-symbolic systems for logical reasoning, and Bayesian neural networks (BNNs) for probabilistic reasoning. Despite their promise, these approaches face significant challenges, including the lack of large-scale reasoning-labeled datasets, high computational costs, and integration hurdles with real-time systems.

Ultimately, the session makes a compelling case for evolving from mere learning to true understanding in wireless signal processing—paving the way for more robust, interpretable, and intelligent communication systems.

 Featured Speakers:  John Cioffi, Reinaldo Valenzuela, Gerhard Fettweis, Rahim Tafazolli, Khaled Letaief, Chengshan Xiao, Alberto Leon-Garcia, Sherman Shen, Wen Tong, Peiying Zhu, Wei Zhang, Kostas Plataniotis

 

 

   
   


 

 

   
   

AI for Communication E2E System Design

 

   
   

 

   
   

Next-Generation_Multiple_Access (pdf))

Next-Generation Multiple Access: From Basic Principles to Modern Architectures | IEEE Journals & Magazine | IEEE Xplore

 

 

Less Data, More Knowledge: Building Next Generation Semantic Communication Networks (pdf)

Less Data, More Knowledge: Building Next-Generation Semantic Communication Networks | IEEE Journals & Magazine | IEEE Xplore

   
   
TACS 

TACS is a leading science technology engineering and top consultancy in the field of nth Generation Fixed or Mobile Wireless Systems and Networks.

TACS scientists engineers and consultants are the first inventors of fixed or mobile packet radio structures in the world for 1G, 2G, 3G, 4G, 5G and 6G wireless systems.

TACS is Pioneer and Innovator of many Communication Signal Processors, Optical Modems, Multi-User Radio Modems, 1G Modems, 2G Modems, 3G Modems, 4G Modems, 5G Modems, 6G Modems, Satellite Modems, PSTN Modems, Cable Modems, PLC Modems, and more..

 
 

TACS 

  • Delivers the insight and vision on technology for strategic decisions on nG (n>1).
  • Assesses technologies and standards and develops architectures for nG.
  • Provides the energy and experience of world-wide leading innovators and experts in nG.
   
   
   
 
 

 


 

   
 

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