Standard Condition Number-Based Detection for MIMO ISAC Systems under Noise Uncertainty

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Hauptverfasser: Obando, Alex, Udupitiya, Tharindu, Atapattu, Saman, Sithamparanathan, Kandeepan
Format: Preprint
Veröffentlicht: 2026
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author Obando, Alex
Udupitiya, Tharindu
Atapattu, Saman
Sithamparanathan, Kandeepan
author_facet Obando, Alex
Udupitiya, Tharindu
Atapattu, Saman
Sithamparanathan, Kandeepan
contents This paper presents a unified analytical and optimization framework for Standard Condition Number (SCN)-based detection in MIMO Integrated Sensing and Communication (ISAC) systems operating under noise uncertainty. Conventional detectors such as the Likelihood Ratio Test (LRT) and Energy Detector (ED) suffer from false-alarm inflation when interference or jamming alters the noise covariance. To overcome this limitation, the SCN detector, defined as the ratio of the largest to smallest eigenvalues of the sample covariance matrix is analytically characterized for the first time in an ISAC setting. Closed-form expressions for the false-alarm and detection probabilities are derived using random matrix theory for a two-antenna sensing receiver and generalized to arbitrary MIMO dimensions. The analysis proves that the SCN maintains a constant false alarm rate (CFAR) property and remains resilient to covariance mismatch, providing theoretical justification for its robustness in dynamic environments. Leveraging these results, a tractable ISAC power-allocation problem is formulated to minimize total detection error subject to communication rate and power constraints, yielding an interpretable sequential solution. Numerical evaluations verify the theory and demonstrate that the proposed SCN detector consistently outperforms LRT and eigenvalue-based benchmarks, particularly under strong interference and jamming typical of modern multiuser networks.
format Preprint
id arxiv_https___arxiv_org_abs_2603_11516
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Standard Condition Number-Based Detection for MIMO ISAC Systems under Noise Uncertainty
Obando, Alex
Udupitiya, Tharindu
Atapattu, Saman
Sithamparanathan, Kandeepan
Signal Processing
This paper presents a unified analytical and optimization framework for Standard Condition Number (SCN)-based detection in MIMO Integrated Sensing and Communication (ISAC) systems operating under noise uncertainty. Conventional detectors such as the Likelihood Ratio Test (LRT) and Energy Detector (ED) suffer from false-alarm inflation when interference or jamming alters the noise covariance. To overcome this limitation, the SCN detector, defined as the ratio of the largest to smallest eigenvalues of the sample covariance matrix is analytically characterized for the first time in an ISAC setting. Closed-form expressions for the false-alarm and detection probabilities are derived using random matrix theory for a two-antenna sensing receiver and generalized to arbitrary MIMO dimensions. The analysis proves that the SCN maintains a constant false alarm rate (CFAR) property and remains resilient to covariance mismatch, providing theoretical justification for its robustness in dynamic environments. Leveraging these results, a tractable ISAC power-allocation problem is formulated to minimize total detection error subject to communication rate and power constraints, yielding an interpretable sequential solution. Numerical evaluations verify the theory and demonstrate that the proposed SCN detector consistently outperforms LRT and eigenvalue-based benchmarks, particularly under strong interference and jamming typical of modern multiuser networks.
title Standard Condition Number-Based Detection for MIMO ISAC Systems under Noise Uncertainty
topic Signal Processing
url https://arxiv.org/abs/2603.11516