Two-Stage Detectors with Multiple Energy Detectors and Adaptive Double Threshold in Cognitive Radio Networks

Bagwari, Ashish; Tomar, Geetam Singh

doi:10.1155/2013/656495

Cited by 63 publications

(28 citation statements)

References 24 publications

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“…These autonomous methods are all simple (ie, they all have a time complexity of O ( N )), they are global‐based methods, and are fully adaptive methods as well, thus making them suitable for investigation in our study. Furthermore, we acknowledge that there are so many ATTs proposed in the literature such as in References ; however, these methods depend typically on larger parameter sets (ie, >2 parameters). Moreover, although these methods are often effective, nevertheless, they were not considered in our study since they are either too highly parametrized or they often depend on the prior knowledge of the SNR level before they can be used.…”

Section: Related Workmentioning

confidence: 99%

Adaptive threshold techniques for cognitive radio‐based low power wide area network

Onumanyi

Abu‐Mahfouz

Hancke

2020

Trans Emerging Tel Tech

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Some low power wide area network (LPWAN) developers such as Sigfox, Weightless, and Nwave, have recently commenced the integration of cognitive radio (CR) techniques in their respective LPWAN technologies, generally termed CR-LPWAN systems. Their objective is to overcome specific limitations associated with LPWANs such as spectra congestion and interference, which in turn will improve the performance of many Internet of Things (IoT)-based applications. However, in order to be effective under dynamic sensing conditions, CR-LPWAN systems are typically required to adopt adaptive threshold techniques (ATTs) in order to improve their sensing performance. Consequently, in this article, we have investigated some of these notable ATTs to determine their suitability for CR-LPWAN systems. To accomplish this goal, first, we describe a network architecture and physical layer model suitable for the effective integration of CR in LPWAN. Then, some specific ATTs were investigated following this model based on an experimental setup constructed using the B200 Universal Software Radio Peripheral kit. Several tests were conducted, and our findings suggest that no single ATT was able to perform best under all sensing conditions. Thus, CR-LPWAN developers may be required to select a suitable ATT only based on the specific condition(s) for which the IoT application is designed. Nevertheless, some ATTs such as the forward consecutive mean excision algorithm, the histogram partitioning algorithm and the nonparametric amplitude quantization method achieved noteworthy performances under a broad range of tested conditions. Our findings will be beneficial to developers who may be interested in deploying effective ATTs for CR-LPWAN systems.

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Section: Related Workmentioning

confidence: 99%

Adaptive threshold techniques for cognitive radio‐based low power wide area network

Onumanyi

Abu‐Mahfouz

Hancke

2020

Trans Emerging Tel Tech

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“…The majority of recent research studies assume that one of the adopted stages is ED. In the other stage, fast Fourier transform (FFT), fuzzy logic, maximum minimum eigenvalue (MME), covariance absolute value (CAV) and waveform detection can be used before or after the ED 19–33 …”

Section: Related Workmentioning

confidence: 99%

Adaptive two‐stage spectrum sensing model using energy detection and wavelet denoising for cognitive radio systems

Fawzi

El‐Shafai

Abd‐Elnaby

et al. 2020

Int J Communication

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This paper presents an efficient adaptive two-stage spectrum sensing model for the cognitive radio (CR) systems. The proposed model combines two wellknown techniques: energy detection (ED) and wavelet denoising (WD). The ED technique is employed to identify the existence of the primary user (PU) signal in the case of high signal-to-noise ratio (SNR) by comparing the received signal with a threshold. In the case of low SNR, the ED technique alone cannot be adopted for decision making about the status of the PU due to the noise impact on the received signals. Hence, the stage of WD is exploited prior to the ED for reducing the noise effect and detecting the PU signal in the presence of noise. The detection performance of the proposed model is compared with those of the ED alone and the previous related two-stage spectrum sensing methods. Simulation results show that the proposed model improves the false alarm rate compared to the ED alone by 36% and 6%, respectively, at low SNRs of −15 and −20 dB. Also, the proposed model yields the smallest detection time compared to the previous two-stage spectrum sensing methods. The proposed model can be used to minimize the probability of false alarm, achieve a better probability of detection, and improve the sensing process in CR systems.

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“…2 dt. Several studies have built on top of the traditional ED by applying a threshold which varies with the SNR [29] or differentiation between various received signal levels through multiple thresholds [30,31]. This way the detector's reliability is improved in the areas of intersection between the distributions of the two hypotheses (see Figure 3).…”

Section: Energy Detectorsmentioning

confidence: 99%

Feature Extraction in Local SpectrumSensing for Next Generation CognitiveRadios � A Review

Ivanov

2020

JMM

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In the context of the currently developed networks for the realization of future communications, the concept of Cognitive Radio (CR) has a significant place. Its implementation in modern ultra-dense networks (UDN) requires the development of novel and improved adaptive solutions for the main functionalities of a CR system. This technology has a great potential for solving the significant spectrum underutilization issue which has been established as characteristic for the traditional communication networks and hence, the continual and substantive research efforts in the recent years. The principal challenge for CRs is the optimization of spectrum utilization without creating unwanted interference for the incumbent (primary) users. Thus, a significant portion of the research is directed towards the vital spectrum sensing functionality. This paper reviews the potential uses of CR in UDN as well as the main approaches for modeling of spectrum sensing with respect to signal detection. The review focuses on local spectrum sensing techniques and presents the strengths and weaknesses of their mathematical definition. Specific attention is given to the channel models which are considered in the literature and to what kinds of features are extracted from the received signal to achieve accurate detection.

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Two-Stage Detectors with Multiple Energy Detectors and Adaptive Double Threshold in Cognitive Radio Networks

Cited by 63 publications

References 24 publications

Adaptive threshold techniques for cognitive radio‐based low power wide area network

Adaptive threshold techniques for cognitive radio‐based low power wide area network

Adaptive two‐stage spectrum sensing model using energy detection and wavelet denoising for cognitive radio systems

Feature Extraction in Local SpectrumSensing for Next Generation CognitiveRadios � A Review

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