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Doubly Constrained Waveform Optimization for Integrated Sensing and Communications.

Zhitong Ni1, Andrew Jian Zhang1, Ren-Ping Liu1

  • 1School of Electrical and Data Engineering, University of Technology, Sydney, NSW 2007, Australia.

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Summary
This summary is machine-generated.

This study optimizes integrated sensing and communication (ISAC) waveforms using mutual information and sum rate constraints. Novel methods address NP-hard problems, enabling flexible system performance for radar and communication.

Keywords:
integrated sensing and communication (ISAC)radar communicationsthreshold constraintwaveform optimization

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Wireless Communications

Background:

  • Integrated Sensing and Communication (ISAC) systems offer dual functionality but require careful waveform design.
  • Existing ISAC waveform optimization often focuses on single metrics, limiting performance flexibility.
  • Simultaneous optimization of sensing and communication metrics under constraints is crucial for advanced ISAC applications.

Purpose of the Study:

  • To investigate threshold-constrained joint waveform optimization for ISAC systems.
  • To simultaneously optimize sensing (mutual information) and communication (sum rate) performance.
  • To develop novel techniques for solving complex, NP-hard optimization problems in ISAC.

Main Methods:

  • Formulated three distinct optimization problems: radar-constrained, communication-constrained, and joint ISAC-constrained.
  • Developed novel gradient descent methods for the radar-only and communication-only constrained problems.
  • Transformed the non-convex joint ISAC optimization problem into a convex one for efficient solving.

Main Results:

  • Successfully optimized ISAC waveforms under simultaneous sensing and communication constraints.
  • Demonstrated the flexibility and effectiveness of the proposed optimization techniques.
  • Validated the proposed solutions through comprehensive numerical and simulation results.

Conclusions:

  • The developed threshold-constrained joint waveform optimization provides significant flexibility for ISAC systems.
  • Novel optimization techniques effectively address the NP-hard nature of ISAC waveform design.
  • The proposed methods offer a viable approach for enhancing ISAC performance in practical applications.