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Joint Communication and Channel Discrimination.

Han Wu1, Hamdi Joudeh1

  • 1Information and Communication Theory Lab, Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.

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|January 8, 2025
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Summary
This summary is machine-generated.

This study explores the communication and sensing trade-off in discrete memoryless channels. It characterizes the optimal balance between channel coding rate and sensing discrimination error exponents under input cost constraints.

Keywords:
capacitydiscrimination exponentsjoint communication and sensing

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Area of Science:

  • Information Theory
  • Wireless Communications
  • Signal Processing

Background:

  • Joint communication and sensing systems integrate data transmission with environmental sensing.
  • Discrete memoryless channels are fundamental models in information theory for analyzing communication limits.
  • Discrimination between channels is crucial for reliable sensing in noisy environments.

Purpose of the Study:

  • To analyze the fundamental trade-offs between communication and sensing performance.
  • To characterize the optimal performance achievable in a joint communication and sensing system.
  • To investigate the impact of channel uncertainty on system performance.

Main Methods:

  • Utilizing information-theoretic tools to analyze error exponents.
  • Deriving performance limits in the asymptotic regime.
  • Employing input cost constraints to model resource limitations.

Main Results:

  • Characterization of the optimal trade-off curve between channel coding rate and sensing error exponents.
  • Identification of the fundamental limits for joint communication and sensing.
  • Demonstration of the impact of channel characteristics on achievable performance.

Conclusions:

  • The study provides a theoretical framework for understanding joint communication and sensing capabilities.
  • Optimal resource allocation is key to balancing communication and sensing objectives.
  • The findings have implications for designing efficient integrated systems.