scholarly journals Spectrum Sensing in Cognitive Radio Using Combined Sequential Energy Detector and Cyclostationary Feature Detector

2016 ◽  
Vol 2 (1) ◽  
pp. 31
Author(s):  
Santosh Poudel ◽  
Heroe Wijanto ◽  
Fiky Y. Suratman
Keyword(s):  
Random Variable ◽  
Energy Detection ◽  
Energy Detector ◽  
Ratio Test ◽  
Feature Detector ◽  
Sample Number ◽  
Low Snr ◽  
Sequential Probability ◽  
Very High ◽  
Average Sample

In the following research, we derive a detector which is based on sequential probability ratio test (SPRT) and it uses Energy Detector (ED) which is followed by Cyclostationary Feature Detector (CFD). ED is a blind sensing technique and it is easy to implement while conceptually simple. However, it is highly affected by interference and noise uncertainties. Therefore, CFD is applied for fine sensing as research has shown that Cyclostationary Feature Detector is more suitable than the energy detection when noise uncertainties are unknown. Our method is novel in trying to derive a sequential Energy Detector and combine it with Cyclostationary Feature Detector for low SNR region where average sample number (ASN) as a random variable may take very high value to achieve a desired performance level for sequential Energy Detector. For this sequential Energy Detector is terminated after it reaches certain cut-off sample number, making it truncated sequential Energy Detector.

scholarly journals Control of Traffic Intensity in Hyperexponential and Mixed Erlang Queueing Systems with a Method Based on SPRT

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Müjgan Zobu ◽  
Vedat Sağlam
Keyword(s):  
Operating Characteristic ◽  
Queueing Systems ◽  
Ratio Test ◽  
Traffic Intensity ◽  
Sample Number ◽  
Average Sample Number ◽  
Phase Type ◽  
Sequential Probability ◽  
Matlab Programming ◽  
Average Sample

The control of traffic intensity is one of the important problems in the study of queueing systems. Rao et al. (1984) developed a method to detect changes in the traffic intensity in queueing systems of the and types based on the Sequential Probability Ratio Test (SPRT). In this paper, SPRT is theoretically investigated for two different phase-type queueing systems which consist of hyperexponential and mixed Erlang. Also, for testing against , Operating Characteristic (OC) and Average Sample Number (ASN) functions are obtained with numerical methods using multipoint derivative equations according to different situations of and type errors. Afterward, numerical illustrations for each model are provided with Matlab programming.

A sequential decision plan for the management of the eastern hemlock looper, Lambdinafiscellariafiscellaria (Lepidoptera: Geometridae), in Newfoundland

1989 ◽  
Vol 19 (7) ◽  
pp. 911-916 ◽  
Author(s):  
E. J. Dobesberger
Keyword(s):  
Negative Binomial ◽  
Eastern Hemlock ◽  
Ratio Test ◽  
Sequential Decision ◽  
Sample Number ◽  
Average Sample Number ◽  
Probability Ratio ◽  
Sequential Probability ◽  
Hemlock Looper ◽  
Average Sample

A sequential decision plan based on Wald's sequential probability ratio test for the negative binomial distribution was derived for eastern hemlock looper (Lambdinafiscellariafiscellaria (Guen.)) egg populations in Newfoundland. An average sample number of not more than six midcrown branches was feasible, and both α and β error rates were defined. Monte Carlo simulation of operating characteristic and average sample number values for static and dynamic K of the negative binomial showed that Wald's sequential probability ratio test was acceptable. More eggs were found on midcrown balsam fir (Abiesbalsamea (L.) Mill.) branches than on other sampling substrates, such as ground mosses (mainly comprising Hylocomiumsplendens (Hedw.) B.S.G., Pleuroziumschreberi (Brid.) Mitt., and Ptiliumcrista-castrensis (Hedw.) De Not.), loose bark from paper birch (Betulapapyrifera Marsh.), and crown lichens (primarily Usnealongissima Ach.).

scholarly journals Spatial Distribution and Development of Sequential Sampling Plans for Diaphorina citri Kuwayama (Hemiptera: Liviidae)

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1434
Author(s):  
Gabriel Díaz-Padilla ◽  
J. Isabel López-Arroyo ◽  
Rafael A. Guajardo-Panes ◽  
Ignacio Sánchez-Cohen
Keyword(s):  
Spatial Distribution ◽  
Sequential Sampling ◽  
Field Evaluation ◽  
Production Costs ◽  
Ratio Test ◽  
Operational Characteristic ◽  
Diaphorina Citri ◽  
Sample Number ◽  
Sampling Plans ◽  
Sequential Probability

Vector control in huanglongbing management has been conducted on a calendar basis resulting in high production costs. We addressed this issue and proposed a sequential sampling plan to support decision making for intervention against Diaphorina citri Kuwayama, which is involved in the transmission of the bacteria Candidatus Liberibacter asiaticus, associated with such lethal disease. We analyzed 3,264,660 records from samples gathered from the Mexican trapping program for the monitoring of D. citri; it included weekly inspection of 86,004 yellow sticky traps distributed in the country. Spatial distribution of the insect, estimation of a common k (kc), and sequential sampling plans based on Sequential Probability Ratio Test (SPRT) were determined. Taylor’s power law coefficients were ≥1 indicating aggregation in the spatial distribution of the insect. Common k ranged from 0.0183 to 0.2253 and varied independently of geographic zone or citrus species. We obtained 18 sequential sampling plans, one for each state. In the Average Sample Number (ASN) function, the minimal number of samples to make a decision ranged from 17 to 65. In the Operational Characteristic (OC) function, probabilities for a correct intervention at the threshold of 0.2 D. citri adults/trap in most cases were above 80%. In a field evaluation, the application of sampling plans yielded savings obtained by reduction in the number of interventions for insect control.

Accuracy of sequential sampling plans based on Wald's sequential probability ratio test

1983 ◽  
Vol 13 (6) ◽  
pp. 1197-1203 ◽  
Author(s):  
Gary W. Fowler
Keyword(s):  
Monte Carlo ◽  
Sequential Sampling ◽  
Sequential Probability Ratio Test ◽  
Ratio Test ◽  
Type I ◽  
Sample Number ◽  
Sampling Plans ◽  
Probability Ratio ◽  
Sequential Probability ◽  
Relative Errors

Monte Carlo operating characteristic (OC) and average sample number (ASN) functions were compared with Wald's OC and ASN equations for sequential sampling plans based on Wald's sequential probability ratio test (SPRT) using the binomial, negative binomial, normal, and Poisson distributions. This comparison showed that the errors inherent in Wald's equations as a result of "overshooting" the decision boundaries of the SPRT can be large. Relative errors increased for the OC and ASN equations as the difference between the null (θ0)) and alternative (θ1) test parameter values increased. Relative errors also increased for the ASN equation as the probabilities of type I (α) and type II (β) errors increased. For discrete distributions, the relative errors also increased as θ0 increased with θ1/θ0 fixed. Wald's equations, in general, overestimate the true error probabilities and underestimate the true ASN. For the values of θ0, θ1, α, and β used in many sequential sampling plans in forestry, Wald's equations may not be adequate. For those cases where the errors in Wald's equations are important compared with the other errors associated with the sampling plan, two alternative Monte Carlo OC and ASN functions are proposed.

scholarly journals Enhanced energy Detection based spectrum sensing for Cognitive Radios

2019 ◽  
Vol 8 (3) ◽  
pp. 8436-8440
Keyword(s):  
Cognitive Radios ◽  
Energy Detection ◽  
Low Complexity ◽  
Radio Spectrum ◽  
Probability Of Detection ◽  
Mobile Systems ◽  
Energy Detector ◽  
Low Snr ◽  
Arbitrary Power ◽  
Sensing Time

Wireless communications play an important role in present days growth of wireless networks which shows the association of mobile systems and internet technologies like IoT in the future which offers various number of services. Different networks with different qualities of networks are available for various areas. In some areas, there will be no connectivity whereas some areas deliver poor connectivity to the network. Hence the spectrum may not be always in use which results in spectral inefficiency. Radio spectrum in the advancement of technology gave an effective solution in terms as Cognitive Radio which manages the spectrum by sensing and sharing effectively. Of all these, sensing plays an important role which detects the vacant band within less time. Energy Detector is one of the sensing methods became more popular because of its low complexity and moderate sensing time. The proposed method is an improvement of Energy Detector with an arbitrary power operation. This reduces the sensing time and improves the recovery performance even at low SNR. The simulation results have proved this for different SNRs ranging from -15db to 5db. The probability of detection was also increased.

scholarly journals Average Sample Number Function for Pareto Heavy Tailed Distributions

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Boukhalfa El-Hafsi
Keyword(s):  
Heavy Tails ◽  
Analytical Formula ◽  
Large Data ◽  
Stable Distributions ◽  
Distribution Functions ◽  
Ratio Test ◽  
Major Drawback ◽  
Sample Number ◽  
Average Sample Number ◽  
Average Sample

The main purpose of this work is shortly to give the average sample number function after a sequential probability ratio test on the index parameter alpha of stable densities, which we give a mean of the number of data required to take decision in the case , we use the fact that the tails of Levy-stable distributions are asymptotically equivalent to a Pareto law for large data. Stable distributions are a rich class of probability distributions that allow skewness and heavy tails and have many intriguing mathematical properties. The lack of closed formulas for densities and distribution functions for all has been a major drawback to the use of stable distributions by practitioners, but few stable distributions have the analytical formula of their densities functions which are Gauss, Levy, and Cauchy.

The use of Wald's sequential probability ratio test to develop composite three-decision sampling plans

1985 ◽  
Vol 15 (2) ◽  
pp. 326-330
Author(s):  
Gary W. Fowler
Keyword(s):  
Monte Carlo ◽  
Negative Binomial ◽  
Sequential Sampling ◽  
Ratio Test ◽  
Sample Number ◽  
Sampling Plans ◽  
Probability Ratio ◽  
Sequential Probability ◽  
Error Probabilities ◽  
Decision Boundaries

Many sequential sampling plans used in forest sampling are composite three-decision plans based on the simultaneous use of two of Wald's sequential probability ratio tests (SPRTs). Wald's operating characteristic (OC) and average sample number (ASN) equations for each SPRT are used to describe the properties of the composite sampling plan. Wald's equations are only approximate because of "overshooting" of the decision boundaries of the SPRTs and the two SPRTs operate simultaneously in the composite plan. Wald's and Monte Carlo OC and ASN functions were developed for (i) two SPRTs used to develop a three-decision composite plan and (ii) the three-decision composite plan based on the negative binomial distribution. Wald's equations, in general, overestimate the true error probabilities and underestimate the true ASN for a given SPRT. Wald's equations are less accurate in describing the properties of the three-decision plan. Monte Carlo functions are more accurate than Wald's functions. Recommendations are made regarding the choice between Wald's and Monte Carlo functions. A Monte Carlo procedure to modify the decision boundaries of the plan to yield actual error probabilities approximately equal to the desired error probabilities is suggested.

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