ScholarWorks@성균관대학교

초록

The growing demand for integrated communication and sensing in next-generation wireless networks has increased interest in intelligent reflecting surfaces (IRS). However, existing spectrum-sharing approaches face challenges in interference management, resource allocation, and deployment costs, particularly with multiple IRSs. To address these issues, this paper investigates a dynamic IRS-assisted communication and sensing setup, where a single IRS supports both a base station and a radar. We propose a novel optimization framework that jointly optimizes beamforming and IRS element allocation using a Weighted Minimum Mean Square Error (WMMSE)-based approach. The IRS dynamically balances its elements between communication and sensing by leveraging signal-to-interference-plus-noise ratio (SINR) trade-offs. Numerical results demonstrate significant improvements in both communication and sensing SINRs under varying system parameters, ensuring efficient spectrum utilization while maintaining performance trade-offs.

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