arXiv subjects

Naima Kaabouch

Publications and source records attributed to Naima Kaabouch.

29 records · Page 2Linked to original sources

arXiv2018

Denoising Signals in Cognitive Radio Systems Using An Evolutionary Algorithm Based Adaptive Filter

Noise originating from several sources in a RF environment degrades the performance of communication systems. In wideband systems, such as cognitive radios, noise at the receiver can originate from non-linearity present in the RF front end, time-varying thermal noise within the receiver radio system, and noise from adjacent network nodes. Several denoising techniques have been proposed for cognitive radios, some of which are applied during spectrum sensing and others to received noisy signal during communication. Examples of some of these techniques used for noise cancellation in received signals are least mean square (LMS) and its variants. However, these algorithms have low performance with non-linear signals and cannot locate a global optimum solution for noise cancellation. Therefore, application of global search optimization techniques, such as evolutionary algorithms, is considered for noise cancellation. In this paper, particle swarm optimization (PSO) and LMS algorithms are implemented and their performances are evaluated. Extensive simulations were performed where Gaussian and non-linear random noise were added to the transmitted signal. The performance comparison was done using two metrics: bit error rate and mean square error. The results show that PSO outperforms LMS under both Gaussian and nonlinear random noise.

eess.SP↗

arXiv2018

A Multidisciplinary Undergraduate Nanoscience and Nanotechnology Program at the University of North Dakota

This paper describes some of the results of a National Science Foundation Nanotechnology Undergraduate Education project that aims to establish a nanoscience and nanotechnology program at the University of North Dakota. The goal is to generate new interest in nanoscience and nanotechnology among engineering and science students and prepare them with the knowledge and skills necessary for the next generation of graduates to compete in the global market and contribute to the nanoscience and nanotechnology field. The project explored several aspects of student learning, including students motivations for investigating nanotechnology through interdisciplinary coursework. To collect this information, a survey was administered to students who enrolled to two nanoscience and nanotechnology courses. Data collected from the survey will be used to improve the design and delivery of future courses as part of constructing a complete nanoscience and nanotechnology curriculum.

physics.ed-ph↗

arXiv2017

Interference Modeling in Cognitive Radio Networks: A Survey

One of the fundamental elements impacting the performance of a wireless system is interference, which has been a long-term issue in wireless networks. In the case of cognitive radio (CR) networks, the problem of interference is tremendously crucial. In other words, CR keeps the important promise of not producing any harmful interference to the primary user (PU) system. Thus, it is essential to investigate the impact of interference caused to the PUs so that its detrimental effect on the performance of the PU system performance is reduced. Study of cognitive interference generally includes developing a model to statistically demonstrate the power of cognitive interference at the PUs, which then can be utilized to examine different performance measures. Having inspected the different models for channel interference present in the literature, it can be obviously seen that interference models have been gradually evolved in terms of complication and sophistication. Although numerous papers can be found in the literature that have investigated different models for interference, to the best of our knowledge, very few publications are available that provide a review of all models and their comparisons. This paper is a collection of state-of-the-art in interference modeling which overviews and compares different models in the literature to provide the valuable insights for researchers when modeling the interference in a specific scenario.

cs.NI↗

arXiv2017

Techniques for Dealing with Uncertainty in Cognitive Radio Networks

A cognitive radio system has the ability to observe and learn from the environment, adapt to the environmental conditions, and use the radio spectrum more efficiently. However, due to multipath fading, shadowing, or varying channel conditions, uncertainty affects the cognitive cycle processes, measurements, decisions, and actions. In the observing step, measurements (i.e., information) taken by the secondary users (SUs) are uncertain. In the next step, the SUs make decisions based on what has already been observed using their knowledge bases, which may have been impacted by the uncertainty, leading to wrong decisions. In the last step, uncertainty can affect the decision of the cognitive radio system, which sometimes can lead to the wrong action. Thus, the uncertainty propagation influences the cognitive radio performance. Therefore, mitigating the uncertainty in the cognitive cycle is a necessity. This paper provides a deep overview of techniques that handle uncertainty in cognitive radio networks.

cs.IT↗

arXiv2016

Matched filter detection with dynamic threshold for cognitive radio networks

-In cognitive radio networks, spectrum sensing aims to detect the unused spectrum channels in order to use the radio spectrum more efficiently. Various methods have been proposed in the past, such as energy, feature detection, and matched filter. These methods are characterized by a sensing threshold, which plays an important role in the sensing performance. Most of the existing techniques used a static threshold. However, the noise is random, and, thus the threshold should be dynamic. In this paper, we suggest an approach with an estimated and dynamic sensing threshold to increase the efficiency of the sensing detection. The matched filter method with dynamic threshold is simulated and its results are compared to those of other existing techniques. Keywords-cognitive radio networks; spectrum sensing; energy detection; matched filter detection; autocorrelation based sensing; estimated dynamic threshold

cs.IT↗

arXiv2016

Automatic Techniques for Gridding cDNA Microarray Images

Microarray is considered an important instrument and powerful new technology for large-scale gene sequence and gene expression analysis. One of the major challenges of this technique is the image processing phase. The accuracy of this phase has an important impact on the accuracy and effectiveness of the subsequent gene expression and identification analysis. The processing can be organized mainly into four steps: gridding, spot isolation, segmentation, and quantification. Although several commercial software packages are now available, microarray image analysis still requires some intervention by the user, and thus a certain level of image processing expertise. This paper describes and compares four techniques that perform automatic gridding and spot isolation. The proposed techniques are based on template matching technique, standard deviation, sum, and derivative of these profiles. Experimental results show that the accuracy of the derivative of the sum profile is highly accurate compared to other techniques for good and poor quality microarray images.

cs.CV↗

arXiv2016

Improvement of the Orthogonal Code Convolution Capabilities Using FPGA Implementation

When data is stored, compressed, or communicated through a media such as cable or air, sources of noise and other parameters such as EMI, crosstalk, and distance can considerably affect the reliability of these data. Error detection and correction techniques are therefore required. Orthogonal Code is one of the codes that can detect errors and correct corrupted data. An n-bit orthogonal code has n/2 1s and n/2 0s. In a previous work these properties have been exploited to detect and correct errors. In this paper we present a new methodology to enhance error detection capabilities of the orthogonal code. The technique was implemented experimentally using Field Programmable Gate Arrays (FPGA). The results show that the proposed technique improves the detection capabilities of the orthogonal code by approximately 50%, resulting in 99.9% error detection, and corrects as predicted up to (n/4-1) bits of error in the received impaired code with bandwidth efficiency.

cs.IT↗

arXiv2016

An Analysis System for DNA Gel Electrophoresis Images Based on Automatic Thresholding an Enhancement

Gel electrophoresis, a widely used technique to separate DNA according to their size and weight, generates images that can be analyzed automatically. Manual or semiautomatic image processing presents a bottleneck for further development and leads to reproducibility issues. In this paper, we present a fully automated system with high accuracy for analyzing DNA and proteins. The proposed algorithm consists of four main steps: automatic thresholding, shifting, filtering, and data processing. Automatic thresholding, used to equalize the gray values of the gel electrophoresis image background, is one of the novel operations in this algorithm. Enhancement is also used to improve poor quality images that have faint DNA bands. Experimental results show that the proposed technique eliminates defects due to noise for average quality gel electrophoresis images, while it also improves the quality of poor images.

cs.CV↗

arXiv2016

Spectrum Occupancy Measurement: An Autocorrelation based Scanning Technique using USRP

This paper presents a technique for scanning and evaluating the radio spectrum use. This technique determines the average occupancy of a channel over a specific duration. The technique was implemented using Software Defined Radio units and GNU Radio software. The survey was conducted in Grand Forks, North Dakota, over a frequency range of 824 MHz to 5.8 GHz. The results of this technique were compared to those of two existing techniques, energy detection and autocorrelation, that were also implemented. The results show that the proposed technique is more efficient at scanning the radio spectrum than the other two techniques.

cs.IT↗

arXiv2016

A Bayesian Network Model of the Bit Error Rate for Cognitive Radio Networks

In addition to serve as platforms for dynamic spectrum access, cognitive radios can also serve as a method for improving the performance of wireless communication systems by smartly adjusting their operating parameters according to the environment and requirements. The uncertainty always present in the environment makes the practical implementation of the latter application difficult. In this paper, we propose a probabilistic graphical model, Bayesian network that captures the causal relationships among the variables bit energy to noise spectral density ratio (EbN0), carrier to interference ratio (C/I), modulation scheme (MOD), Doppler phase shift (Dop_Phi), and bit error rate (BER). BER indicates how the communication link is performing. The goal of our proposed Bayesian network is to use the BER as evidence in order to infer the behavior of the other variables, so the cognitive radio can learn how the conditions of the environment are, and based on that knowledge make better informed decisions. This model along with the method used to build it are described in this paper.

cs.IT↗

arXiv2016

Alternative Technique to Asymmetry Analysis-Based Overlapping for Foot Ulcer Examination: Scalable Scanning

Asymmetry analysis based on the overlapping of thermal images proved able to detect inflammation and, predict foot ulceration. This technique involves three main steps: segmentation, geometric transformation, and overlapping. However, the overlapping technique, which consists of subtracting the intensity levels of the right foot from those of the left foot, can also detect false abnormal areas if the projections of the left and right feet are not the same. In this paper, we present an alternative technique to asymmetry analysis-based overlapping. The proposed technique, scalable scanning, allows for an effective comparison even if the shapes and sizes of the feet projections appear differently in the image. The tested results show that asymmetry analysis- based scalable scanning provides fewer false abnormal areas than does asymmetry analysis -based overlapping.

cs.CV↗