Order-Statistic Based Spectrum Sensing for Cognitive Radio
TL;DR: Simulation results show that order statistics based sensing considerably outperforms both energy detection and anderson darling based sensing in an Additive White Gaussian Noise (AWGN) channel; especially in a lower signal to noise ratio region.
Abstract: Spectrum sensing for cognitive radio is challenging. In this letter, a spectrum sensing method based on quintiles of Order-Statistics is proposed. We derive the test statistic and evaluate the performance of the proposed method by Monte Carlo simulations. Simulation results show that order statistics based sensing considerably outperforms both energy detection and anderson darling based sensing in an Additive White Gaussian Noise (AWGN) channel; especially in a lower signal to noise ratio region.
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TL;DR: An overview of potential network architecture and several promising techniques which could be employed in the future 5G systems are presented and the state-of-art and implementation issue of these techniques are addressed.
Abstract: The fourth generation (4G) mobile communication systems are offering service worldwide steadily. Although 4G systems could be loaded with much more services and data than previous systems, there is still a dramatic gap between the peoples practical requirements and what can be offered by the 4G technologies. Consequently, the research and development for the fifth generation (5G) systems have already been started. This article presents an overview of potential network architecture and highlights several promising techniques which could be employed in the future 5G systems. These techniques include non-orthogonal multiple access (NOMA), massive multiple input and multiple output (MIMO), cooperative communications and network coding, full duplex (FD), device-to-device (D2D) communications, millimeter wave communications, automated network organization, cognitive radio (CR), and green communications. The state-of-art and implementation issue of these techniques are also addressed.
178 citations
01 Oct 2017
TL;DR: The performance of proposed sensing scheme is evaluated on several real-world primary signals of various radio technologies and it has been found out that for all those radio technologies the proposed scheme outperforms the classical energy detection and the improved energy detection.
Abstract: Spectrum sensing is a key aspect of Cognitive Radio (CR) The main requirement in CR systems is the ability to sense the primary signal accurately and rapidly In this paper, a novel hybrid spectrum sensing scheme in CR is proposed which considers the hypothesis problem as a binary classification problem The proposed scheme is a combination of classical energy detection, Likelihood Ratio Test statistic (LRS-G2) and Artificial Neural Network (ANN) The scheme utilises energy from energy detection and Zhang test statistic from LRS-G2 as features to train the ANN while ANN provides the adaptive learning and stable performance to the scheme The performance of proposed sensing scheme is evaluated on several real-world primary signals of various radio technologies and it has been found out that for all those radio technologies the proposed scheme outperforms the classical energy detection and the improved energy detection
54 citations
Cites methods from "Order-Statistic Based Spectrum Sens..."
...A number of different GoF based sensing schemes have been proposed in the literature like Anderson Darling (AD) test [9], Ordered Statistics (OS) [10], Kolmogorov-Smirnov (KS) [11], [12] and Likelihood Ratio Statistics (LRS-G2) [13], [14]....
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27 Apr 2015
TL;DR: This paper proposes an efficient resource allocation and link adaptation algorithm to support carrier aggregation functionality for downlink 5G LTE-Advanced (LTE-A) network and shows clearly that the algorithm outperforms state-of-the-art algorithms.
Abstract: Carrier aggregation has been introduced by 3rd Generation Partnership project (3GPP) in order to meet the IMT-Advanced requirements Using carrier aggregation, multiple component carriers with a different bandwidth, dispersed within intra or inter bands can be simultaneously utilised to provide higher data rates, better coverage and lower latency resulting a better user experience However, carrier aggregation functionality requires modification to the radio resource management function of the network In this paper, we propose an efficient resource allocation and link adaptation algorithm to support carrier aggregation functionality for downlink 5G LTE-Advanced (LTE-A) network We consider a non-guaranteed bit rate bearers (best effort traffic), which can be used for non realtime applications such as file downloads Most of the existing work considered resource allocation, component carrier selection and link adaptation as separate problems We define a joint radio resource management problem with carrier aggregation functionality and propose a sub-optimal solution with a low computational complexity Simulation results show clearly that our algorithm outperforms state-of-the-art algorithms
36 citations
Cites background from "Order-Statistic Based Spectrum Sens..."
...Since LTE Release 10, the concept of CA for both LTEA and cognitive radio networks [3] has gained significant attention in both academia and industry [2], [4], [5]....
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TL;DR: In this article, a new spectrum sensing method based on the goodness of fit test of the energy of the received samples with a chi-square distribution was proposed and the test statistic is derived and the performance of the proposed method is evaluated by Monte Carlo simulations.
Abstract: In cognitive radio, spectrum sensing is a challenging task. Proposed is a new spectrum sensing method based on the goodness of fit test of the energy of the received samples with a chi-square distribution. The test statistic is derived and the performance of the proposed method is evaluated by Monte Carlo simulations. It is shown that the proposed spectrum sensing method outperforms the conventional energy detection method without increasing the complexity of the sensing.
30 citations
TL;DR: Through Monte Carlo simulations, it is shown that for a class of practically relevant fading channel and primary signal models, especially in low SNR regime, the proposed detector achieves a higher probability of detection than the energy detector and the order statistics-based detector.
Abstract: We propose a novel goodness-of-fit detection scheme for spectrum sensing, based on differential entropy in the received observations. The noise distribution is known to deviate from the Gaussian in many practical communication settings. We, therefore, permit that the noise process follows the generalized Gaussian distribution, which subsumes Gaussian and Laplacian as special cases. We obtain, in closed form, the distribution of the test statistic under the null hypothesis and compute the detection threshold that satisfies a constraint on the probability of false alarm. Furthermore, we derive a lower bound on the probability of detection in a general scenario, using the entropy power inequality. Through Monte Carlo simulations, we show that for a class of practically relevant fading channel and primary signal models, especially in low SNR regime, our detector achieves a higher probability of detection than the energy detector and the order statistics-based detector. We also demonstrate that the adverse effect of noise variance uncertainty is much less with the proposed detector compared with that of the energy detector.
19 citations
Cites background or methods or result from "Order-Statistic Based Spectrum Sens..."
...Through Monte Carlo simulations, we showed that the proposed detector (DED) outperforms the energy detector (ED) and the order statistic based detector (OSD) in terms of enhanced probability of detection under various settings....
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...See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. simulations, we demonstrate that our detector outperforms ED and OSD considering several practically relevant models for the primary signal and the fading, and also show that the noise variance uncertainty [16] has less adverse effects on its performance (§ IV), as compared to the ED and OSD....
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...It should be noted that the performance of OSD in all cases is only trivial, i.e., pd = p f , and hence will be omitted from comparisons henceforth....
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...In [4], the authors proposed an order statistic based detector (OSD) and showed...
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...In [4], the authors proposed an order statistic based detector (OSD) and showed Manuscript received March 5, 2016; revised April 19, 2016; accepted April 22, 2016....
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References
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TL;DR: In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented and the cooperative sensing concept and its various forms are explained.
Abstract: The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.
4,812 citations
"Order-Statistic Based Spectrum Sens..." refers background in this paper
...However ED based sensing (EDsensing) performance deteriorates significantly if the received SNR is low [1]....
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...However, the introduction of opportunistic users employing cognitive radio technology inevitably increases the interference and thus degrades the Quality of Service (QoS) of the PUs [1]....
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...A number of spectrum sensing techniques are available in literature, for a good review refer to [1]....
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TL;DR: It is shown by both analysis and numerical results that under the same sensing conditions and channel environments, Anderson-Darling sensing has much higher sensitivity to detect an existing signal than energy detector-based sensing, especially in a case where the received signal has a low signal-to-noise ratio (SNR) without prior knowledge of primary user signals.
Abstract: One of the most important challenges in cognitive radio is how to measure or sense the existence of a signal transmission in a specific channel, that is, how to conduct spectrum sensing. In this letter, we first formulate spectrum sensing as a goodness of fit testing problem, and then apply the Anderson-Darling test, one of goodness of fit tests, to derive a sensing method called Anderson-Darling sensing. It is shown by both analysis and numerical results that under the same sensing conditions and channel environments, Anderson-Darling sensing has much higher sensitivity to detect an existing signal than energy detector-based sensing, especially in a case where the received signal has a low signal-to-noise ratio (SNR) without prior knowledge of primary user signals.
126 citations
"Order-Statistic Based Spectrum Sens..." refers background in this paper
...However ED based sensing (EDsensing) performance deteriorates significantly if the received SNR is low [1]....
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...T represents the transpose operation....
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TL;DR: In this article, a test-statistic based on quantiles of order-statistics is proposed, which compares favorably with the Kolmogorov-Smirnov (K-S) and Anderson-Darling (A-D) test statistics.
Abstract: Our new method uses order statistics to judge the fit of a distribution to data. A test-statistic based on quantiles of order-statistics compares favorably with the Kolmogorov-Smirnov (K-S) and Anderson-Darling (A-D) test statistics. The performance of this new goodness-of-fit test statistic is examined with simulation experiments. For certain hypothesis tests, the test statistic is more powerful than the K-S and A-D test statistics. The new test statistic is calculated using a computer algebra system because of the need to compute exact distributions of order statistics.
45 citations
01 Jan 2010
6 citations
03 Mar 2010
TL;DR: A novel suite of transmit opportunity detection methods that effectively exploit the white/gray space in high traffic packet networks and presents a radically different paradigm to exploit the excess Signal-to-Noise ratio regime.
Abstract: Cognitive Radio Networks (CRNs) operate on the principle of opportunistically exploiting unused capacity in the primary network via Dynamic Spectrum Sensing. In this paper we propose a novel suite of transmit opportunity detection methods that effectively exploit the white/gray space in high traffic packet networks. We present a radically different paradigm to exploit the excess Signal-to-Noise ratio regime in which the primary network usually operates via a modification of the Interference Temperature concept. The proposed method is based on robust and rapid detection of changes in the primary network statistics through the use of a novel Parallelized Goodness-of- Fit test. The instantaneous transmit margin afforded by the primary network is dynamically determined and the CRN backs off whenever it detects that it is beginning to interfere with the primary network. We have implemented the proposed method on a CRN testbed that coexists with a large scale IEEE 802.11 primary network and demonstrate its excellent performance through extensive real world experimental results. We show that we can obtain more than 95 % probability of detection of interference while the probability of not detecting a valid transmit opportunity is less than 20 % for detection times of 400–1000 ms.
5 citations