Showing papers on "Cumulative distribution function published in 2023"
TL;DR: In this paper , the authors investigated the physical layer security for RIS-aided wireless communication systems, where one RIS is deployed to assist the communications between a pair of transmitter (Alice) and receiver (Bob), under a passive eavesdropper (Eve) attack.
Abstract: In this article, the physical layer security (PLS) is investigated for reconfigurable intelligent surface (RIS)-aided wireless communication systems, where one RIS is deployed to assist the communications between a pair of transmitter (Alice) and receiver (Bob), under a passive eavesdropper (Eve) attack. For the Eve, different from the bounded channel state information uncertainty model, the distribution of the Eve’s location is introduced into the wiretap link. In the proposed system, considering that the Eve can overhear signals transmitted from Alice or reflected by the RIS, two scenarios are studied for RIS-aided secure communication systems: one is that the Eve distributes close to Alice without the RIS orientation, and the other is that the Eve locates close to Bob and in the presence of the RIS. After investigating the probability distribution functions of the Eve’s location and the wiretap link, the novel cumulative density functions (CDFs) of the received signal-to-noise ratios (SNRs) at the Eves are, respectively, derived for the two considered scenarios, taking into account the effects of RIS reflection coefficients, pathloss, and Eve’s location distribution. The closed-form expressions for the probability of the nonzero secrecy capacity and the ergodic secrecy capacity are obtained, providing insights into the impact of the Eve’s location uncertainty and the RIS design on the secrecy performance. Moreover, based on the derived CDFs for received SNRs at Eves, the secrecy outage probabilities are, respectively, analyzed. Specifically, under the constraint of the secrecy outage probability, the closed forms of the minimum required SNRs at Bob and the number of RIS elements are also obtained. Simulation and analytical results corroborate the derived expressions and reveal the tradeoff between the system’s energy efficiency and the number of RIS elements.
6 citations
TL;DR: In this paper , the authors investigated whether the estimates of a simple cumulative opportunity measure are significantly different from those made using advanced gravity-based measures to understand if the former can be a substitute for the latter in practice and if a certain threshold of travel time can be recommended for different regions.
4 citations
TL;DR: In this paper , a probabilistic model for the threshold stress intensity factor range is developed, which is a critical parameter in infinite fatigue life design under material flaws, and the model is based on the proposed concept of probability of propagation in the probablistic framework, allowing for deriving the probability density function of the threshold intensity factor.
3 citations
TL;DR: The Global Likelihood Sampler (GLS) as discussed by the authors uses the GL bootstrap to assess the Monte Carlo error and shows that the empirical cumulative distribution function of the samples uniformly converges to the target distribution under some conditions.
Abstract: Drawing samples from a target distribution is essential for statistical computations when the analytical solution is infeasible. Many existing sampling methods may be easy to fall into the local mode or strongly depend on the proposal distribution when the target distribution is complicated. In this article, the Global Likelihood Sampler (GLS) is proposed to tackle these problems and the GL bootstrap is used to assess the Monte Carlo error. GLS takes the advantage of the randomly shifted low-discrepancy point set to sufficiently explore the structure of the target distribution. It is efficient for multimodal and high-dimensional distributions and easy to implement. It is shown that the empirical cumulative distribution function of the samples uniformly converges to the target distribution under some conditions. The convergence for the approximate sampling distribution of the sample mean based on the GL bootstrap is also obtained. Moreover, numerical experiments and a real application are conducted to show the effectiveness, robustness, and speediness of GLS compared with some common methods. It illustrates that GLS can be a competitive alternative to existing sampling methods. Supplementary materials for this article are available online.
3 citations
TL;DR: In this article , the authors proposed a new privatization mechanism based on a naive theory of additive perturbations on a probability using wavelets, such as a noise perturbs the signal of a digital image sensor.
Abstract: A naive theory of additive perturbations on a continuous probability distribution is presented. We propose a new privatization mechanism based on a naive theory of a perturbation on a probability using wavelets, such as a noise perturbs the signal of a digital image sensor. The cumulative wavelet integral function is defined and builds up the perturbations with the help of this function. We show that an arbitrary distribution function additively perturbed is still a distribution function, which can be seen as a privatized distribution, with the privatization mechanism being a wavelet function. It is shown that an arbitrary cumulative distribution function added to such an additive perturbation is still a cumulative distribution function. Thus, we offer a mathematical method for choosing a suitable probability distribution to data by starting from some guessed initial distribution. The areas of artificial intelligence and machine learning are constantly in need of data fitting techniques, closely related to sensors. The proposed privatization mechanism is therefore a contribution to increasing the scope of existing techniques.
2 citations
TL;DR: In this article , a quantile regression model based on a parametric distribution is proposed to estimate covariate-related response variables that are measured on the unit interval frequently arise in diverse studies when index and proportion data are of interest.
Abstract: Covariate-related response variables that are measured on the unit interval frequently arise in diverse studies when index and proportion data are of interest. A regression on the mean is commonly used to model this relationship. Instead of relying on the mean, which is sensitive to atypical data and less general, we can estimate such a relation using fractile regression. A fractile is a point on a probability density curve such that the area under the curve between that point and the origin is equal to a specified fraction. Fractile or quantile regression modeling has been considered for some statistical distributions. Our objective in the present article is to formulate a novel quantile regression model which is based on a parametric distribution. Our fractile regression is developed reparameterizing the initial distribution. Then, we introduce a functional form based on regression through a link function. The main features of the new distribution, as well as the density, distribution, and quantile functions, are obtained. We consider a brand-new distribution to model the fractiles of a continuous dependent variable (response) bounded to the interval (0, 1). We discuss an R package with random number generators and functions for probability density, cumulative distribution, and quantile, in addition to estimation and model checking. Instead of the original distribution-free quantile regression, parametric fractile regression has lately been employed in several investigations. We use the R package to fit the model and apply it to two case studies using COVID-19 and medical data from Brazil and the United States for illustration.
2 citations
TL;DR: In this article , a new channel state information (CSI) feedback scheme based on probability distribution is proposed for massive multiple-input multiple-output (MIMO) systems, where the real and imaginary parts of the channel elements are divided into several groups and sorted in ascending order.
Abstract: In this paper, a new channel state information (CSI) feedback scheme based on probability distribution is proposed for massive multiple-input multiple-output (MIMO) systems. In the proposed scheme, the real and imaginary parts of the channel elements are divided into several groups and sorted in ascending order. The sorted channel elements are approximated to a cumulative distribution function of a predefined probability distribution, and parameters representing the probability distributions are obtained for each group. The generated CSI, including the representing parameters and original ordering information, is fed back to the base station (BS). Finally, the channel vectors are reconstructed based on the CSI from the BS. It has been verified that the proposed scheme outperforms the conventional CSI feedback schemes in terms of the sum rate under a similar feedback overhead with low computational complexity.
2 citations
TL;DR: In this paper , a probabilistic approach is proposed to determine an analytical expression for the cumulative distribution function (CDF) of the active storage as a function of rainfall moments, water demand and the mean number of consecutive storm events in a deficit sub-period.
Abstract: Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude and the variability of rainfall profiles and the size of the demand. Given the random nature of the variables involved in the hydrological process, probability theory is a suitable technique for active storage estimation. This research proposes a probabilistic approach to determine an analytical expression for the cumulative distribution function (CDF) of the active storage as a function of rainfall moments, water demand and the mean number of consecutive storm events in a deficit sub-period. The equation can be used by developers to decide on the storage capacity required at a desired non-exceedance probability and under a preset water demand. The model is validated through a continuous simulation of the tank behavior using rainfall time series from Milan (Northern Italy).
2 citations
TL;DR: In this article , an alternative approach was developed in which used 150 and 170 MELCOR calculation cases to develop bootstrapped artificial neural network (ANN) models which predict single FOM and two FOMs, respectively.
Abstract: This study is concerned with uncertainty analysis of MELCOR simulation of a hypothetical severe accident initiated by station blackout (SBO) in a Nordic boiling water reactor (BWR). The hydrogen mass from cladding oxidation and the vessel failure timing in the accident are selected as the figures of merit (FOMs) in this study. As a conventional approach of uncertainty analysis, 456 cases with random sampling of 31 MELCOR input parameters are executed by the code to produce the empirical cumulative distribution functions (CDFs) and the empirical 95th percentiles of the FOMs. Given the sufficient sample cases, uncertainty analyses through two nonparametric methods at various orders, i.e., the Wilks' method and the Wald & Guba's method, can then be performed to obtain the distributions of 95/95 estimates (95th percentiles estimated at a 95% confidence level) of single FOM and two FOMs. However, the conventional approach turns out to be time consuming and computationally expensive since many sample cases require iterative tuning of MELCOR input to restart and finish calculations. To overcome this issue encountered in the conventional approach of uncertainty analysis, an alternative approach is developed in the present study, in which 150 and 170 MELCOR calculation cases are used to develop bootstrapped artificial neural network (ANN) models which predict single FOM and two FOMs, respectively. The bootstrapped ANN models are then employed in uncertainty analyses through the two nonparametric methods of 95/95 estimates mentioned above. The comparative results show that the alternative approach can reproduce the distributions of 95/95 estimates for both single FOM and two FOMs with less computational costs. Moreover, while the Wilks' method or the Wald & Guba's method at a very high order (e.g., 100th order) can be used in the alternative approach to produce 95/95 estimates closer to the empirical 95th percentile, it is practically impossible to do so in the conventional approach due to unaffordable computational cost of excessive MELCOR runs. Hence, it can be concluded that the alternative approach of uncertainty analysis is not only effective (much less MELCOR cases with least fixing of unsuccessful runs), but also enabling high-order nonparametric methods for 95/95 estimates.
1 citations
TL;DR: In this paper , a new methodology was proposed to compute the probability density function (PDF) and cumulative distribution function (CDF) of the elevation angle, θ, for diverse Earth Stations (ES) locations.
Abstract: The elevation angle θ is relevant for the Low Earth orbit (LEO) satellite communications since it is always changing its relative position with respect to fixed Earth stations (ES’s), and this affects the link length and received power, PR. This article provides a new methodology to compute the probability density function (PDF) and cumulative distribution function (CDF) of the elevation angle, θ, for diverse ES locations. This methodology requires as input parameters an ES latitude, ϕ, an orbit inclination value, i, and an orbit altitude, h. The elevation angle is characterized through a well known random variable, which facilitates the computation of the first and second-order statistics, and helps to determine the expected value and measures of dispersion of the angle θ for a particular ES location. The proposed methodology allows an easy and quick calculation of the elevation angle’s CDF, facilitating comparisons against CDF’s of more ES’s located at different latitudes, and longitudes, λ; as well as the comparisons of CDF’s of the elevation angle produced by different orbits. Extensive simulation results are summarized in a small table, which allows computation of the elevation angle’s CDF and PDF for multiple ES locations without requiring of simulations and statistical fitting. Finally, the proposed methodology is validated through an extensive error analysis that show the suitability of the obtained results to characterize the elevation angle.
1 citations
TL;DR: In this paper , an extended lifetime probability distribution based on the alpha power transformation is proposed, which is referred to as the Alpha Power Topp-Leone (APTL) distribution.
Abstract: This paper presents an extended lifetime probability distribution based on the alpha power transformation. We refer to the proposed distribution as “the Alpha Power Topp-Leone (APTL) distribution”. Mathematical properties of the APTL distribution such as the density and cumulative distribution functions, survival and hazard rate functions, quantile function, median, moments and its relative measures, probability weighted moment, moment generating function, Renyi entropy, and the distribution of order statistics were derived. The method of maximum likelihood estimation was employed to estimate the unknown parameters of the APTL distribution. Finally, we used two real data sets obtained from the literature to illustrate the applicability of the APTL distribution in real-life data fitting.
TL;DR: In this article , the cumulative impact of tourist infrastructure on the habitat of wild reindeer (Rangifer t. tarandus), a nearly-threatened species highly sensitive to anthropogenic disturbance, is investigated.
Abstract: The concept of cumulative impacts is widespread in policy documents, regulations, and ecological studies, but quantification methods are still evolving. Infrastructure development usually takes place in landscapes with preexisting anthropogenic features. Typically, their impact is determined by computing the distance to the nearest feature only, thus ignoring the potential cumulative impacts of multiple features. We propose the cumulative ZOI approach to assess whether and to what extent anthropogenic features lead to cumulative impacts. The approach estimates both effect size and zone of influence (ZOI) of anthropogenic features and allows for estimation of cumulative effects of multiple features distributed in the landscape. First, we use simulations and an empirical study to understand under which circumstances cumulative impacts arise. Second, we demonstrate the approach by estimating the cumulative impacts of tourist infrastructure in Norway on the habitat of wild reindeer (Rangifer t. tarandus), a nearly-threatened species highly sensitive to anthropogenic disturbance. Simulations show that analyses based on the nearest feature and our cumulative approach are indistinguishable in two extreme cases: when features are few and scattered and their ZOI is small, and when features are clustered and their ZOI is large. Empirical analyses revealed cumulative impacts of private cabins and tourist resorts on reindeer, extending up to 10 and 20 km, with different decaying functions. Although the impact of an isolated private cabin was negligible, the cumulative impact of ‘cabin villages’ could be much larger than that of a single large tourist resort. Focusing on the nearest feature only underestimates the impact of ‘cabin villages’ on reindeer. The suggested approach allows us to quantify the magnitude and spatial extent of cumulative impacts of point, linear, and polygon features in a computationally efficient and flexible way and is implemented in the oneimpact R package. The formal framework offers the possibility to avoid widespread underestimations of anthropogenic impacts in ecological and impact assessment studies and can be applied to a wide range of spatial response variables, including habitat selection, population abundance, species richness and diversity, community dynamics, and other ecological processes.
TL;DR: Wang et al. as discussed by the authors proposed an improved algorithm based on the original two-dimensional multifractal detrended fluctuation analysis (2D MF-DFA) that involves increasing the number of cumulative summations in the computational steps.
Abstract: In this paper, we propose an improved algorithm based on the original two-dimensional (2D) multifractal detrended fluctuation analysis (2D MF-DFA) that involves increasing the number of cumulative summations in the computational steps of 2D MF-DFA. The proposed method aims to modify the distribution of the generalized Hurst exponent to ensure that skin lesion image features are extracted based on enhanced multifractal features. We calculate the generalized Hurst exponent using 0, 1, or 2 cumulative summation processes. A support vector machine (SVM) is adopted to examine the classification performance under these three conditions. Computation shows that the process involving two cumulative summations achieves an accuracy, sensitivity, and specificity of [Formula: see text], [Formula: see text], and [Formula: see text], respectively, which indicates that its performance is much better than with 0 and 1 cumulative summations.
TL;DR: In this paper , a new generalization of one parameter Lindely distribution is proposed, called "GOLD distribution", which is a mixture distribution of Gamma distributions with fixed scale parameter and variable shape parameter.
Abstract: In this paper, a new generalization of one parameter Lindely distribution is proposed. The new distribution is a mixture distribution of Gamma distributions with fixed scale parameter and variable shape parameter. The distribution is called 'GOLD Distribution' as it is a generalization for several distributions such as exponential, Lindely, Sujatha, Amarendra, Devya and Shambhu distributions. The probability density and cumulative density functions are derived. Also, the statistical properties of the GOLD distribution are discussed. Parameter estimation using the maximum likelihood and the method of moments are given. Moreover, an illustration of the usefulness of the GOLD distribution in survival data analysis is discussed based on a real lifetime data.
TL;DR: In this paper , a comprehensive analysis on the performance of integrating RIS into full-duplex (FD) cellular or Internet of Things (IoT) networks in both realistic Rician and Nakagami fadings is presented.
Abstract: Intelligent reflecting surface (IRS) has been deemed as an energy and spectral-efficient technology, that can potentially enhance network coverage and transmission reliability, with minimum impact on transceivers' complexity. Motivated by this, we develop a comprehensive analysis on the performance of integrating IRS into full-duplex (FD) cellular or Internet of Things (IoT) networks in both realistic Rician and Nakagami fadings. Firstly, in the context of reciprocal channels in Rician fadings, we derive the closed-form approximations of the users' outage probability (OP) and ergodic capacity (EC), under the non-central Chi-square distribution assumption on the signal-to-interference-plus-noise ratio (SINR). Further following by the Gamma distribution assumption on the SINR, we derive the cumulative distribution function (CDF) expression of the user's SINR, which is then leveraged to obtain simple yet effective closed-form expressions in terms of OP and EC. Subsequently, in Nakagami fading scenarios with the reciprocal and non-reciprocal channels, the closed forms of both users' OP and EC are obtained. Finally, the correctness of all the theoretical expressions is verified through substantial Monte Carlo simulations. The results indicate that the OP and EC deduced from Gamma distribution exhibit the fairly precise results for the arbitrary number of IRS elements, especially in Nakagami fadings.
TL;DR: The complementary gamma zero-truncated Poisson distribution (CGZTP) as mentioned in this paper combines the distribution of the maximum of a series of independently identical gamma-distributed random variables with zero truncated poisson random variables.
Abstract: Numerous lifetime distributions have been developed to assist researchers in various fields. This paper proposes a new continuous three-parameter lifetime distribution called the complementary gamma zero-truncated Poisson distribution (CGZTP), which combines the distribution of the maximum of a series of independently identical gamma-distributed random variables with zero-truncated Poisson random variables. The proposed distribution’s properties, including proofs of the probability density function, cumulative distribution function, survival function, hazard function, and moments, are discussed. The unknown parameters are estimated using the maximum likelihood method, whose asymptotic properties are examined. In addition, Wald confidence intervals are constructed for the CGZTP parameters. Simulation studies are conducted to evaluate the efficacy of parameter estimation, and three real-world data applications demonstrate that CGZTP can be an alternative distribution for fitting data.
TL;DR: In this article , the authors considered a scenario of a decode-and-forward (DaF) wireless system supporting the communication of an unmanned aerial vehicle (UAV) with a ground-control-station (GCS) through an intelligent reflecting surface (IRS).
Abstract: In this article, we consider a scenario of a decode-and-forward (DaF) wireless system supporting the communication of an unmanned aerial vehicle (UAV) with a ground-control-station (GCS) through an intelligent reflecting surface (IRS). Particularly, the UAV moves according to the three-dimensional (3D) random way point model at low altitude in a complex urban environment. However, a stationary relay-station (RS) decodes and forwards the UAV’s signal over an IRS-aided virtual line-of-sight (LoS) link to a GCS. The highly dynamic and terrain-dependent UAV-to-RS channel follows the Beaulieu-Xie fading model. However, the RS-to-IRS and IRS-to-GCS links enjoy clear LoS; thus, follow the Rice fading model. We derive new closed-form expressions for the probability density functions (PDFs) and the cumulative distribution functions (CDFs). Then based on the derived statistical expressions, several performance metrics including outage probability, average bit error rate, and ergodic channel capacity are derived in closed-forms. Additionally, simple and accurate approximated expressions in the high signal-to-noise ratio regime are also provided. The analytical results are validated through some representative numerical examples and supported by Monte-Carlo simulation results.
TL;DR: In this paper , the authors proposed a new class of probability distributions as an extended version of the exponential hyper-Poisson distribution and Weibull Poisson distribution, which they termed as exponential hyper poisson distribution.
Abstract: Here we propose a new class of probability distributions as an extended version of the exponential hyper-Poisson distribution and Weibull Poisson distribution. We investigate several important aspects of the distribution through deriving expressions for its probability density function (pdf), cumulative distribution function, survival function, failure rate function, pdf of the order statistics, r-th raw moments, etc. The method of maximum likelihood estimation procedures along with EM algorithm is discussed for estimating the parameters of the distribution and a test procedure is suggested for testing the significance of the additional parameters of the proposed model. The use of the proposed distribution is illustrated through real-life data sets. Further, a brief simulation study is carried out for evaluating the performance of the estimators obtained for the parameters of the distribution.
TL;DR: A distribution is a set of information on a variable as discussed by the authors , which can be used to define and compute significant variables, such as an observation's probability, as well as to show the relationships between observations in the domain.
Abstract: A distribution is a set of information on a variable. When these data are normally grouped in size order from least to largest, they may then be visually represented. In fact, it is fairly simple to comprehend statistical distributions in terms of functional relationships. Simply put, a data variable is thought of as being coupled with another data variable or several data variables into specific functional relationships, the majority of which can be reflected in the coordinate axes. Once the distribution function has been built, it may be swiftly used to define and compute significant variables, such as an observation's probability, as well as to show the relationships between observations in the domain. The distribution of statistics is very broad, it goes deep into various fields of study, with different specialties and models combined. The process of discovering them is also different, and again, different distributions apply to different scenarios. When faced with different mathematical models, Mathematicians should choose the most suitable distribution method to calculate the probability density function, cumulative distribution function, and calculate the probability and expected value, so as to correctly understand the model. The following article will focus on different definitions of statistical distributions and their origins.
01 Jan 2023
TL;DR: In this paper , the authors simplify an existing dynamic programming solution to achieve an exponential-in-d factor improvement in both time and space complexity over known methods for the non-i.i.d. setting.
Abstract: Order statistics play a fundamental role in the construction of empirical distribution functions, which are fundamental to empirical process theory and non- parametric statistics. In some applications, it is desirable to compute the joint cumulative distribution function (cdf) of d order statistics exactly. Efficient algorithms to compute this quantity are known when the data are i.i.d.; however, the task becomes significantly more challenging when relaxing either the identically distributed or the independence assumption. Existing methods for the non-i.i.d. setting obtain the joint cdf indirectly, by first computing and then aggregating over the marginal distributions. In this paper, we simplify an existing dynamic programming solution to achieve an exponential-in-d factor improvement in both time and space complexity over known methods. We detail the independent, non-identical setting, and then outline how our method extends to more general settings (e.g., dependent random variables) in an online appendix.
TL;DR: In this paper , an unmanned aerial vehicle (UAV)-assisted dual-hop FSO communication system equipped with amplify-and-forward protocol at the relay node is proposed, and closed-form expressions of the probability density function (PDF) and cumulative distribution function (CDF) for the proposed communication system, in terms of the Meijer-G function.
Abstract: Free space optical (FSO) communication has recently aroused great interest in academia due to its unique features, such as large transmission band, high data rates, and strong anti-electromagnetic interference. With the aim of evaluating the performance of an FSO communication system and extending the line-of-sight transmission distance, we propose an unmanned aerial vehicle (UAV)-assisted dual-hop FSO communication system equipped with amplify-and-forward protocol at the relay node. Specifically, we consider impairments of atmospheric absorption, pointing errors, atmospheric turbulence, and link interruptions due to angle-of-arrival fluctuations in the relay system. The Gamma-Gamma and Malaga distributions are used to model the influence of atmospheric turbulence on the source-to-UAV and UAV-to-destination links, respectively. We derive closed-form expressions of the probability density function (PDF) and cumulative distribution function (CDF) for the proposed communication system, in terms of the Meijer-G function. Based on the precise PDF and CDF, analytical expressions for the outage probability, average bit error rate, and ergodic capacity are proposed with the aid of the extended generalized bivariate Fox's H function. Finally, we show that there is a match between the analytical results and numerical results, and we analyze the influence of the system and channel parameters on the performance.
26 Mar 2023
TL;DR: In this article , hand effects on cellphone antennas at 5G millimeter-wave frequencies are evaluated through measurements using hand phantoms and are compared with results from electromagnetic simulations, and the spherical coverage and corresponding cumulative distribution function are calculated.
Abstract: In this manuscript, hand effects on cellphone antennas at 5G millimeter-wave frequencies are evaluated through measurements using hand phantoms and are compared with results from electromagnetic simulations. First, two configurations of a dual-polarized 4-element linear antenna array operating at 28 GHz are introduced. One-hand and two-hand physical phantoms and their numerical models for electromagnetic simulations are illustrated. Then, the array evaluation metric, i.e., spherical coverage, is introduced to assess statistics of realized gain across the solid angle. Next, antenna measurement setups are implemented for the two antenna arrays combined with the two physical hand phantoms. Finally, the spherical coverage and the corresponding cumulative distribution function are calculated. Differences in the realized gains derived from simulated and measured antenna arrays are about 1 dB at the median levels of the cumulative distribution. The differences are comparable to those observed when real hands are used in measurements instead of phantom hands [1].
TL;DR: In this paper , the performance of a free-space optical communication system with non-zero-boresight pointing errors was analyzed using the doubly inverted Gamma-Gamma (IGGG) turbulence channel model.
Abstract: In this paper, the recently proposed doubly inverted Gamma-Gamma (IGGG) turbulence channel model is considered to analyze the performance of a free-space optical communication system. To this end, the probability density function (PDF) and cumulative distribution function (CDF) of the irradiance fluctuations of an optical wave propagating through an IGGG turbulence channel under nonzero-boresight pointing errors are derived. Furthermore, the PDF and CDF under zero-boresight pointing errors are obtained as a special case. To study the impact of nonzero-boresight pointing error parameters and turbulence condition on the system performance, exact closed-form expressions for outage probability, bit error rate, and average capacity under intensity modulation/direct detection are derived. Besides, asymptotic analysis is provided which help us to identify the diversity gain of the system. The analytical analyzes are verified through numerical and Monte-Carlo simulation results.
TL;DR: In this article , the authors consider an uplink access for non-standard access in a non-cooperative manner, and propose an access control system based on the concept of non-uniform access.
Abstract: 본 논문에서는 하나의 송신 안테나를 갖는 두 개의 단말과 다중 수신 안테나를 갖는 기지국을 갖는 상향링크 비직교 다중 접속 시스템을 고려하고, 아웃티지 확률을 개선하기 위하여 순차적 선택 결합 기법을 제시한다. 여기서, 순차적 선택 결합 기법은 수신 안테나 선택 기법과 순차적 간섭 제거 기법을 기반으로 한다. 또한, 순차적 선택 결합 기법을 이용하는 상향링크 비직교 다중 접속 시스템에서 각 단말에 대한 아웃티지 확률의 수학적 분석을 제시한다. 특히, 최종적인 아웃티지 확률의 수식은 채널의 누적 분포 함수와 확률 밀도 함수로 표현되어 다양한 채널의 확률 함수에 대하여 아웃티지 확률을 구할 수 있다. 본 논문에서는 레일레이 채널을 가정하여 아웃티지 확률의 수학적 분석 결과와 시뮬레이션 결과를 비교하여 아웃티지 확률의 수식을 검증하고, 수신 안테나 수의 증가에 따른 순차적 선택 결합 기법의 아웃티지 확률이 개선됨을 보인다. In this paper, we consider an uplink non-orthogonal multiple access (NOMA) system with two mobile stations (MSs) with a single transmit antenna and a base station with multiple receive antennas. We present a successive selection combining (SC) scheme to improve the outage probability (OP), where the successive SC scheme is based on the receive antenna selection and successive interference cancellation schemes. In addition, we present the mathematical analysis of the OP for each MS in the uplink NOMA system using successive SC scheme. Especially, an mathematical expression for the OP includes the cumulative distribution functions and the probability density functions of channels, and thus we can obtain the OP for the probability functions of various channels. In this paper, comparing the analytical and simulation results of the OP under Rayleigh fading channels, we verify the mathematical expression for the OP, and show that the OP for the successive SC scheme improves with an increase in the number of receive antennas.
01 Feb 2023
TL;DR: In this article , an extended fractional cumulative past entropy (EFCPE) is proposed, which is a dual of the EFCRE, which depends on the logarithm of fractional order and the cumulative distribution function (CDF).
Abstract: Very recently, extended fractional cumulative residual entropy (EFCRE) has been proposed by Foroghi et al., (2022). In this paper, we introduce extended fractional cumulative past entropy (EFCPE), which is a dual of the EFCRE. The newly proposed measure depends on the logarithm of fractional order and the cumulative distribution function (CDF). Various properties of the EFCPE have been explored. This measure has been extended to the bivariate setup. Furthermore, the conditional EFCPE is studied and some of its properties are provided. The EFCPE for inactivity time has been proposed. In addition, the extended fractional cumulative paired ϕ-entropy has been introduced and studied. The proposed EFCPE has been estimated using empirical CDF. Furthermore, the EFCPE is studied for coherent systems. A validation of the proposed measure is provided using logistic map. Finally, an application is reported.
TL;DR: In this paper , the authors investigated a wireless mobile communication system with a cooperative network operating over a mobile-to-mobile (M2M) fading channel in the presence of co-channel interference and derived closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the SIR at the input of the destination station.
Abstract: In this paper, we investigate a wireless mobile communication system with a cooperative network operating over a mobile-to-mobile (M2M) fading channel in the presence of co-channel interference. Since there is no direct line of sight between the source (S) and the destination (D) due to various obstacles, the signal transmission takes place by using a relay (R). We modeled and represented the desired signal and co-channel interference by using the Nakagami-m fading distribution from the source (S) to the relay (R), as well as from the relay (R) to the destination (D). As the popularity of M2M communication has increased in 5G cellular networks, the performance analysis of the proposed system is of great importance. We derived closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the signal-to-interference ratio (SIR) at the input of the destination station. Based on the cumulative distribution function (CDF), we also evaluated the outage probability (Pout) of the proposed communication system. In addition, we derived a closed-form approximate expression for the level crossing rate (LCR) by using the Laplace approximation formula for the three-fold integral. Validity of the derived theoretical results we approved by Monte Carlo simulations.
05 Jan 2023
TL;DR: In this article , the authors proposed a Bayesian model with enhanced performance on statistical datasets by incorporating the concept of empirical copulas to compute the joint probability distribution of features present in the data.
Abstract: In this paper, we propose a Bayesian model with enhanced performance on statistical datasets by incorporating the concept of Empirical copulas to compute the joint probability distribution of features present in the data. Copulas are defined as cumulative distribution functions deemed popular in highdimensional statistical applications since they easily enable one to model and estimate the distribution of random vectors by estimating the marginals and copulae separately. The key idea of this method is to replace the joint probability, which is defined as the probability of occurrence of two or more simultaneous events, with the cumulative distribution generated by the nonparametric empirical copula function and utilize it on bivariate and multivariate data to assess the performance of the model thus generated. Through extensive research on the topic of nonparametric empirical copulas and tuning the model with various smoothing techniques, we have achieved significant accuracy with a more robust statistical hold in the predictive analysis of different datasets in comparison to the simple Gaussian Naïve Bayes technique.
TL;DR: In this article , a family of consistent tests, derived from a characterization of the probability generating function, is proposed for assessing Poissonity against a wide class of count distributions, which includes some of the most frequently adopted alternatives to the Poisson distribution.
Abstract: Abstract A family of consistent tests, derived from a characterization of the probability generating function, is proposed for assessing Poissonity against a wide class of count distributions, which includes some of the most frequently adopted alternatives to the Poisson distribution. Actually, the family of test statistics is based on the difference between the plug-in estimator of the Poisson cumulative distribution function and the empirical cumulative distribution function. The test statistics have an intuitive and simple form and are asymptotically normally distributed, allowing a straightforward implementation of the test. The finite sample properties of the test are investigated by means of an extensive simulation study. The test shows satisfactory behaviour compared to other tests with known limit distribution.
TL;DR: In this paper , the performance of a reconfigurable intelligent surface (RIS) aided communication system under ultra-reliable low-latency communication (URLLC) constraints, where the secrecy performance for communication with multiple legitimate users (D), scheduled one at a time, in presence of eavesdropper (E) is analyzed.
Abstract: This work investigates the performance of a reconfigurable intelligent surface (RIS) aided communication system under ultra-reliable low-latency communication (URLLC) constraints, where the secrecy performance for communication with multiple legitimate users (D), scheduled one at a time, in presence of eavesdropper (E) is analyzed. The outage probability and block error rate (BLER) at D and E are derived for infinite and finite blocklength transmissions assuming that the direct communication links between source (S)-D and S-E exist. The expressions for the asymptotic outage probability, secrecy capacity, secrecy outage probability and secure BLER are also obtained. The new expressions for the probability density function (PDF) and the cumulative distribution function (CDF) for the difference of phases of two Nakagami-m distributed channel envelopes are derived. To validate the correctness of the derived analytical expressions and to analyze the impact of various system parameters including the number of RIS meta-atoms, the magnitude of reflection coefficient, transmit signal-to-noise ratio (SNR) threshold, and quantized phase-shifts, Monte-Carlo simulations are used. The performance of the proposed system is compared with that of the decode and forward relay-based system. It is also shown that RIS significantly improves the performance at D, whereas degrading the same for E.