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In this paper, we target at cognitively detecting the presence of the primary user (PU) as well as recognizing PU's signal modulation. Since the existing modulation classification methods rely on fixed sensing period which may waste time when the modulations are easier to distinguish, we propose an automatic modulation classification (AMC) approach using likelihood-based (LB) and feature- based (FB)...
Eigenvalue-based detection is one of the most promising techniques proposed for spectrum sensing in cognitive radio as it is insensitive to the noise uncertainty problem. However, the eigenvalue-based detection schemes presented so far rely on asymptotic assumptions that are not suitable for many realistic scenarios, thus determining a substantial degradation of detection performance. In this paper,...
While wireless sensor networks (WSNs) are typically targeted at large-scale deployment, due to many practical or inevitable reasons, a WSN may not always remain connected. In this paper, we consider the possibility that a WSN may be spatially separated into multiple subnetworks. Data gathering, which is a fundamental mission of WSN, thus may rely on a mobile mule (ldquomulerdquo for short) to conduct...
Fully exploiting the phase and magnitude information in received data is crucial to the detection of cognitive radio signals, and this is usually done in the time domain. In fact, the same set of information can also be exploited in the frequency domain in the form of power spectrum. The most appealing one is the multitaper spectrum (MTS) estimator, which enjoys a high estimation accuracy and relatively...
Likelihood function decomposition is a technique to coordinate deployed fields of multiple diverse heterogeneous sensors and for the automated processing of large volumes of multisensor data. It is an innovative new concept that is potentially useful in many of the kinds of nonlinear problems that arise in sensor fields used for detection, classification, and localization. Algorithms derived via the...
Sequential sensing algorithms are developed for OFDM-based hierarchical cognitive radio (CR) systems. Secondary users sense multiple sub-bands simultaneously for possible spectrum availabilities under hard miss-detection constraints to prevent interference to the primary users. Accounting for the fact that the sensing time overhead can often be significant, a performance metric is developed based...
We combine concepts from numerous papers to provide a derivation and description of a generalized probabilistic multi-hypothesis tracker (PMHT) that can track multiple targets in a cluttered environment, utilizing multiple sensors and feature measurements, if available. We also provide a simplified method of performing the maximization step of the algorithm when multiple sensors are used, a consistent...
For wireless sensor networks, it is an effective approach for energy conservation in wireless sensor networks to keep the most of redundant sensors asleep while the remaining nodes stay active to maintain both sensing coverage and network connectivity, i.e., to form the minimal connected cover set. A novel concept named "square grid partition" is proposed, and based on the good characteristics...
This paper presents a novel iterative greedy reconstruction algorithm for practical compressed sensing (CS), called the sparsity adaptive matching pursuit (SAMP). Compared with other state-of-the-art greedy algorithms, the most innovative feature of the SAMP is its capability of signal reconstruction without prior information of the sparsity. This makes it a promising candidate for many practical...
We propose a light weight algorithm to classify cane-toads, a non-native invasive amphibian species in Australia as well as other native frog species, based on their vocalizations using sharply resource-constrained acoustic sensors. The goal is to enable fast in-network frog classification at the resource-constrained sensors so as to minimize energy consumption of the sensor network by reducing the...
This paper focuses on the design of medium access control protocols for cognitive radio networks. The scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands within parts of the radio spectrum having multiple bands is first considered. In this scenario, the availability probability of each channel is unknown a priori to the cognitive...
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