Physical Layer Security of Cooperative NOMA for IoT Networks under I/Q Imbalance

In this paper, we investigate the reliability and security of cooperative dual-hop non-orthogonal multiple access (NOMA) for internet-of-thing (IoT) networks, in which the transceivers consider a detrimental factor of in-phase and quadrature-phase imbalance (IQI). The communication between the source and destination is accomplished through a decode-and-forward (DF) relay in the presence of an eavesdropper. In order to characterize the performance of the considered system, exact analytical expressions for the outage probability (OP) and intercept probability (IP) are derived in closed-form. Furthermore, to better understanding the performance of the considered system, we further derive the asymptotic expressions of OP in the high signal-to-noise ratio (SNR) regime and IP at the high main eavesdropping ratio (MER) region. A large number of analysis and Monte Carlo simulation results show that the existence of IQI usually increases the corresponding OP and reduces the IP, which means that reduces the reliability of the system and improves the security. In addition, the provided results provide useful insights into the trade-off between reliability and security of secure cooperative communication systems

A Robust Method for GPS/BDS Pseudorange Differential Positioning Based on the Helmert Variance Component Estimation

The use of global navigation satellite system (GNSS) is entering a new era of joint positioning based on the use of multifrequencies and multimodes. Ensuring the correct weighting of observations from each system and satellite has become a key problem during real-time positioning. This paper addresses the issue of weights of observations as well as the quality control of GPS/BDS pseudoranges in the context of real-time relative positioning. Thus, in the first place, the Helmert variance component estimation (VCE) is used to determine the relative weighting of observations from the two systems, and then, we introduce robustness estimation theory and construct a new method. The method is resistant to the influence of outliers in the observations by selecting weight iterations. To do this, we selected GPS/BDS observation data at baseline lengths of 40 km, 46 km, and 64 km for verification and analysis. Experimental results show that, in terms of the relative positioning of medium-to-long baseline based on GPS/BDS pseudorange observations, when observed values incorporate large gross errors, our method can reduce the weighting of suspicious or abnormal values and weaken their impact on positioning solutions, so that the positioning results will not appear to have large deviation

Testing optimally weighted combination of variants for hypertension

© 2014 Zhao et al.; licensee BioMed Central Ltd. Testing rare variants directly is possible with next-generation sequencing technology. In this article, we propose a sliding-window-based optimal-weighted approach to test for the effects of both rare and common variants across the whole genome. We measured the genetic association between a disease and a combination of variants of a single-nucleotide polymorphism window using the newly developed tests TOW and VW-TOW and performed a sliding-window technique to detect disease-susceptible windows. By applying the new approach to unrelated individuals of Genetic Analysis Workshop 18 on replicate 1 chromosome 3, we detected 3 highly susceptible windows across chromosome 3 for diastolic blood pressure and identified 10 of 48,176 windows as the most promising for both diastolic and systolic blood pressure. Seven of 9 top variants influencing diastolic blood pressure and 8 of 9 top variants influencing systolic blood pressure were found in or close to our top 10 windows

Central and peripheral changes in the retina and choroid in patients with diabetes mellitus without clinical diabetic retinopathy assessed by ultra-wide-field optical coherence tomography angiography

BackgroundTo explore the central and peripheral retinal and choroidal changes in diabetic patients without clinical diabetic retinopathy (DM-NoDR) using ultra-wide-field swept-source optical coherence tomography angiography (UWF-SS-OCTA).Methods67 DM-NoDR eyes and 32 age-matched healthy eyes were recruited. Retinal and choroidal parameters, including qualitative retinal microangiopathy, vessel flow (VFD) and linear density (VLD), thickness, and volume, were measured in the central and peripheral areas of the 24 × 20 mm2 UWF-SS-OCTA images.ResultsDM-NoDR eyes had significantly more nonperfusion area and capillary tortuosity than controls in the central and peripheral areas (p < 0.05). The presence of central capillary tortuosity was associated with higher levels of serum creatinine (OR 1.049, 95%CI 1.001–1.098; p = 0.044) and blood urea nitrogen (OR 1.775, 95%CI 1.051–2.998; p = 0.032) in DM-NoDR eyes. For DM-NoDR eyes versus controls, VFD in the 300-μm annulus around the foveal avascular zone, superficial capillary plexus (SCP), and full retina, and SCP-VLD significantly decreased, while VFD in the deep capillary plexus (DCP), retinal thickness, and retinal volume increased (p < 0.05). Analysis in the central and peripheral areas recapitulated all these findings, except for decreased peripheral thickness and volume and no difference in peripheral DCP-VFD. In DM-NoDR eyes, choriocapillaris-VFD, choroidal thickness, and choroidal volume increased in the central area, while VFD in the large and medium choroidal vessel layer decreased in the whole image (p < 0.05).ConclusionRetinal and choroidal changes already existed in the central and/or peripheral areas of DM-NoDR eyes. UWF-SS-OCTA, enabling the visualization of the peripheral fundus area, is a promising image technique for the early detection of fundus changes in DM-NoDR patients

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s)

Deep Learning Based Secure MIMO Communications with Imperfect CSI for Heterogeneous Networks

Perfect channel state information (CSI) is required in most of the classical physical layer security techniques, while it is difficult to obtain the ideal CSI due to the time varying wireless fading channel. Although imperfect CSI has a greatly impact on the security of MIMO communications, deep learning is becoming a promising solution to handle the negative effect of imperfect CSI. In this work, we propose two types of deep learning based secure MIMO detectors for heterogeneous networks, where the macro base station (BS) chooses the null-space eigenvectors to prevent information leakage to the femto BS. Thus, the bit error rate of the associated user is adopted as the metric to valuate the system performance. With the help of deep convolutional neural networks (CNNs), the macro BS obtains the refined version from the imperfect CSI. Simulation results are provided to validate the proposed algorithms. The impacts of system parameters, such as the correlation factor of imperfect CSI, the normalized doppler frequency, the number of antennas are investigated in different setup scenarios. The results show that considerable performance gains can be obtained from the deep learning based detectors compared with the classical maximum likelihood algorithm

Secure Analysis of Multi-Antenna NOMA Networks Under I/Q Imbalance

This paper investigates the reliability and security performance of the downlink non-orthogonal multiple access (NOMA) networks over Nakagami-m fading channels, where the base station (BS) aims to communicate with multi-antenna NOMA users in the presence of a multi-antenna eavesdropper. To be more practical, a detrimental factor at both transmitter and receiver is considered, namely in-phase and quadrature-phase imbalance (IQI). To further improve the reliability and security of the considered networks, the selection combining (SC) algorithm at the receiver is taken into account. More specifically, the exact analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived in closed-form. To obtain a better understanding of the influence for the IQI parameters on the system performance, the asymptotic behaviors for the outage probabilities (OPs) in the high signal-to-noise ratio (SNR) region are analyzed. Based on the asymptotic results, the diversity order of the considered system are obtained and discussed. The numerical results are presented to verify the validity of the theoretical analysis