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arXiv · 2506.09439

Eigenvalue-Based Detection in MIMO Systems for Integrated Sensing and Communication

Alex Obando·Saman Atapattu·Prathapasinghe Dharmawansa·Akram Hourani·Kandeepan Sithamparanathan
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Abstract

This paper considers a MIMO Integrated Sensing and Communication (ISAC) system, where a base station simultaneously serves a MIMO communication user and a remote MIMO sensing receiver, without channel state information (CSI) at the transmitter. Existing MIMO ISAC literature often prioritizes communication rate or detection probability, typically under constant false-alarm rate (CFAR) assumptions, without jointly analyzing detection reliability and communication constraints. To address this gap, we adopt an eigenvalue-based detector for robust sensing and use a performance metric, the total detection error, that jointly captures false-alarm and missed-detection probabilities. We derive novel closed-form expressions for both probabilities under the eigenvalue detector, enabling rigorous sensing analysis. Using these expressions, we formulate and solve a joint power allocation and threshold optimization problem that minimizes total detection error while meeting a minimum communication rate requirement. Simulation results demonstrate that the proposed joint design substantially outperforms conventional CFAR-based schemes, highlighting the benefits of power- and threshold-aware optimization in MIMO ISAC systems.

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Alex Obando, Saman Atapattu, Prathapasinghe Dharmawansa, Akram Hourani, Kandeepan Sithamparanathan. 2025-06-11. Eigenvalue-Based Detection in MIMO Systems for Integrated Sensing and Communication. https://arxiv.org/abs/2506.09439

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