Spectrum sensing for cognitive radio requires effective monitoring of wide bandwidths, which translates into high-rate sampling. Traditional spectrum methods employing high-precision analog-to-digital converters (ADCs) result in increased power consumption and expensive hardware costs. In this paper, we explore blind utilizing one-bit ADCs. We derive a closed-form detector based on Rao's test demonstrate its equivalence with the second-order eigenvalue-moment-ratio test. Furthermore,...

Target detection is an important problem in multiple-input multiple-output (MIMO) radar. Many existing target algorithms were proposed without taking into consideration the quantization error caused by analog-to-digital converters (ADCs). This paper addresses of for MIMO radar with one-bit ADCs and derives a Rao's test-based detector. The method has several appealing features: 1) it closed-form detector; 2) allows us to handle sign measurements straightforwardly; 3) there are approximations...

Subspace-based high-resolution algorithms for direction-of-arrival (DOA) estimation have been developed large-scale adaptive antenna arrays. However, its prerequisite step, namely, source enumeration, has not yet addressed. In this paper, a new approach is devised in the framework of Bayesian information criterion (BIC) to provide reliable detection signal number general asymptotic regime, where m, n → ∞ and m/n c ∈ (0, ∞), with m being numbers antennas snapshots, respectively. particular,...

In this work, the volume-based method for spectrum sensing is analyzed, which able to provide desirable properties of constant false-alarm rate, robustness against deviation from independent and identically distributed (IID) noise being free uncertainty. By computing first second moments signal-absence signal-presence hypotheses together with using Gamma distribution approximation, we derive accurate analytic formulae detection probabilities IID situations. This enables us develop...

Hadamard ratio test is a well-known approach to robust signal detection in multivariate analysis. Recently, it has been exploited for spectrum sensing cognitive radio, but its performance not yet completely analyzed. This work devoted accurate analysis of the method sensing. By computing first and second exact negative moments signal-presence hypothesis along with employing Beta distribution approximation, we derive analytic formulae probability. enables us theoretically evaluate behavior...

Although noncircular (NC) signals are frequently encountered in wireless communications, their statistical property has not yet been utilized state-of-the-art methods for spectrum sensing. In this paper, a variant of Hadamard (HDM) ratio test is devised to exploit the NC primary sensing, which named NC-HDM algorithm. As approach able full and handle deviations from independent identically distributed (IID) noise, it superior algorithms detection accuracy and/or robustness. Moreover,...

One-bit analog-to-digital converter (ADC), performing signal sampling as an extreme simple comparator, is overwhelming technology for spectrum sensing due to its low-cost, low-power consumptions and high rate. In this letter, we propose a novel one-bit approach based on the eigenvalue moment ratio (EMR), which has been proved be highly efficient conventional multi-antenna in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math...

Covariance matrix recovery is a topic of great significance in the field one-bit signal processing and has numerous practical applications. Despite its importance, conventional arcsine law with zero threshold incapable recovering diagonal elements covariance matrix. To address this limitation, recent studies have proposed use non-zero clipping thresholds. However, relationship between estimation error sampling not yet known. In article, we undertake an analysis mean squared by computing...

Locally most powerful invariant test (LMPIT) for sphericity of Gaussian vectors has been derived by Ramírez et al. Nevertheless, the decision threshold LMPIT is not accurate and its detection performance yet addressed. In this paper, performed target in multiple-input multiple-output (MIMO) radar, theoretical as well probability are accurately determined. Utilizing asymptotic expansion approach, we calculate null distribution a function central chi-square distributions, resulting precise...

Usually, it is very difficult to determine the exact distribution for a test statistic. In this paper, asymptotic distributions of locally most powerful invariant independence complex Gaussian vectors are developed. particular, its cumulative function (CDF) under null hypothesis approximated by chi-squared CDFs. Moreover, CDF corresponding non-null expressed in terms non-central CDFs close hypothesis, and as well derivatives far hypothesis. The results turn out be accurate fitting their...

This letter addresses the problem of signal detection in additive correlated noise whose covariance matrix is Toeplitz. Particularly, we design a novel approach framework generalized likelihood ratio test, which maximum (ML) estimate Toeplitz needed. Since there are no closed-form expressions for this ML estimate, resort to inverse iterative algorithm. The proposed detector surpasses existing methods power and enjoys constant false-alarm rate property. Besides, accurate asymptotic null...

Accurate source number detection with one-bit quantized data is of considerable interest in array signal processing, as quantization offers low cost and complexity practical systems. Conventional model-driven methods, e.g., Akaikes information criterion minimum description length, suffer from severe performance degradation when implemented only the sign available. In this paper, well-known Arcsine Law explored to recover a normalized covariance matrix, then model-aided neural network...

One-bit sampling has emerged as a promising technique in multiple-input multiple-output (MIMO) radar systems due to its ability significantly reduce data volume and processing requirements. Nevertheless, current detection methods have not adequately addressed the impact of colored noise, which is frequently encountered real scenarios. In this paper, we present novel method that accounts for noise MIMO systems. Specifically, derive Rao's test by computing derivative likelihood function with...

Large Vision-Language Models (LVLMs) evolve rapidly as Language (LLMs) was equipped with vision modules to create more human-like models. However, we should carefully evaluate their applications in different domains, they may possess undesired biases. Our work studies the potential behavioral biases of LVLMs from a finance perspective, an interdisciplinary subject that jointly considers and psychology. We propose end-to-end framework, data collection new evaluation metrics, assess LVLMs'...

John's test, which is also known as the locally most invariant test for sphericity of Gaussian variables, one frequently used methods in multichannel signal detection. The application requires closed-form and accurate formula to set threshold according a prescribed false alarm rate. Asymptotic expansion powerful method deriving expressions detectors large samples. However, existing asymptotic analysis real-valued case not accurate, causing obtained rate deviate from preset value. This work...

Detection of cyclostationary (CS) signals has been addressed by means generalized likelihood ratio test criteria. However, an accurate maximum estimator requires the estimation cycle period (CP) as a priori information, which not yet correctly in literature. In this correspondence, CP is devised under information theoretic criterion(ITC) framework for long observation regime. particular, we formulate asymptotic log-likelihood function discrete frequency domain. From evidence that direct...