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Summary

This study optimizes Integrated Sensing and Communication (ISAC) systems by jointly designing transmit covariance matrices. The method balances communication data rates with sensing accuracy, crucial for future wireless networks.

Keywords:
ISACcondition numbermulti-user MIMOresource optimizationtrade-off analysis

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Area of Science:

  • Wireless Communication
  • Signal Processing
  • Information Theory

Background:

  • Integrated Sensing and Communication (ISAC) is a key technology for future wireless networks, merging communication and sensing.
  • A major challenge in ISAC is balancing communication data rate and sensing accuracy, particularly in multi-user environments.

Purpose of the Study:

  • To investigate the joint design of transmit signal covariance matrices for ISAC systems.
  • To optimize the sum data rate while maintaining required sensing performance.

Main Methods:

  • Formulation of a constrained optimization problem to maximize communication sum-rate.
  • Allocation of transmit covariance matrices under sensing-related constraints.
  • Utilization of convex optimization tools for principled trade-off management.

Main Results:

  • The proposed method effectively balances communication and sensing performance in ISAC systems.
  • Achieved near-optimal communication data rates while satisfying sensing requirements.
  • Demonstrated the impact of covariance matrix design on sensing accuracy and data rate.

Conclusions:

  • The developed approach provides an effective solution for managing the inherent trade-offs in ISAC.
  • This work contributes to the advancement of efficient and high-performance ISAC system design.
  • The findings are crucial for realizing the full potential of ISAC in next-generation wireless networks.