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Search results for: NETWORK PERFORMANCE
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Traffic Type Influence on QoS Network Performance of Streaming Traffic Class
PublicationFeasibility study on QoS routing proved that the traffic type influence the network performance. The performance is defined here as a number of packets serviced by the network. In the paper additional element - buffers lengths used in service system was verified in terms of dependencies with routing performance. We present results obtained by simulation for many simulation scenarios. Analysis was done for two different network...
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Simulator for Performance Evaluation of ASON/GMPLS Network
PublicationThe hierarchical control plane network architecture of Automatically Switched Optical Network with utilization of Generalized Multi-Protocol Label Switching protocols is compliant to next generation networks requirements and can supply connections with required quality of service, even with incomplete domain information. Considering connection control, connection management and network management, the controllers of this architecture...
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Cryptographic Protocols' Performance and Network Layer Security of RSMAD
PublicationW artykule omówiono architekturę bezpieczeństwa warstwy sieciowej Radiowego Systemu Monitorowania i Akwizycji Danych z urządzeń fotoradarowych (w skrócie RSMAD). Bezpieczeństwo w warstwie sieciowej tego systemu jest zapewniane przede wszystkim dzięki wykorzystaniu Virtual Private Network (w skrócie VPN). W tym celu zaimplementowano dwa protokoły IPsec i L2TP.Zastosowane mechanizmy ochrony danych, w tym typy i parametry VPNów zostały...
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The Performance of ASON/GMPLS Network with Hierarchical Control Plane Structure
PublicationThe paper regards the problem of ASON/GMPLS network performance with hierarchical control plane structure in condition of incomplete domain network information. The authors propose the hierarchical ASON/GMPLS control plane architecture, which fulfills the requirements of modern optical networks and allows to control the multidomain network with requirement quality of service. The authors examine the scalability and properties of...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Performance Evaluation of a Multidomain IMS/NGN Network Including Service and Transport Stratum
PublicationThe Next Generation Network (NGN) architecture was proposed for delivering various multimedia services with guaranteed quality. For this reason, the elements of the IP Multimedia Subsystem (IMS) concept (an important part of 4G/5G/6G mobile networks) are used in its service stratum. This paper presents comprehensive research on how the parameters of an IMS/NGN network and traffic sources influence mean Call Set-up Delay (E(CSD))...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Optimal programming of critical sections in modern network processors under performance requirements.
PublicationPrzegląd konstrukcji i zastosowań metod programowania sekcji krytycznych w nowoczesnych procesorach sieciowych rodziny Intel IXP. Porównanie wydajnościowe w formie tabeli.
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Personal Branding—A New Competency in the Era of the Network Economy. Corporate Brand Performance Implications
PublicationPrimary assets of the network economy are information, network, re-lationships, knowledge, and a virtual environment. The competency of personal branding exercised by knowledge workers, also thought of as knowledge producers, is becoming a natural consequence of the business environment where the significance of hierarchies is constantly decreasing. Knowledge workers are powerful as never be-fore and can exist as separate actors...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Performance and Security Testing for Improving Quality of Distributed Applications Working in Public/Private Network Environments
PublicationThe goal of this dissertation is to create an integrated testing approach to distributed applications, combining both security and performance testing methodologies, allowing computer scientist to achieve appropriate balance between security and performance charakterstics from application requirements point of view. The constructed method: Multidimensional Approach to Quality Analysis (MA2QA) allows researcher to represent software...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublicationIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
PublicationIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were...
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublicationThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublicationBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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SPIE Conference on Performance and Control of Network Systems
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Intelligent turbogenerator controller based on artifical neural network
PublicationThe paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...
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Neural network agents trained by declarative programming tutors
PublicationThis paper presents an experimental study on the development of a neural network-based agent, trained using data generated using declarative programming. The focus of the study is the application of various agents to solve the classic logic task – The Wumpus World. The paper evaluates the effectiveness of neural-based agents across different map configurations, offering a comparative analysis to underline the strengths and limitations...
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Pathological brain network activity: memory impairment in epilepsy
PublicationOur thinking, memory and cognition in general, relies upon precisely timed interactions among neurons forming brain networks that support cognitive processes. The surgical evaluation of drug-resistant epilepsy using intracranial electrodes provides a unique opportunity to record directly from human brain and to investigate the coordinated activity of cognitive networks. In this issue of Neurology®, Kleen and colleagues1 implicate...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Multi Queue Approach for Network Services Implemented for Multi Core CPUs
PublicationMultiple core processors have already became the dominant design for general purpose CPUs. Incarnations of this technology are present in solutions dedicated to such areas like computer graphics, signal processing and also computer networking. Since the key functionality of network core components is fast package servicing, multicore technology, due to multi tasking ability, seems useful to support packet processing. Dedicated...
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Evaluation of a sat-type fairness mechanism implemented in a dual-ring network
PublicationThe fairness problem was presented. Popular fairness concepts and measures were shown. The RPR fairness mechanism and the SAT mechanism were described. A modification of the SAT algorithm, adapted to the possibilities of Ethernet cards used for implementation of a dual-ring RPR-based network, was proposed. Performance of the proposed modification was measured. Jain's and Chen's fairness indexes were calculated. Effectiveness comparison...
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Distributed state estimation using a network of asynchronous processing nodes
PublicationWe consider the problem of distributed state estimation of continuous-time stochastic processes using a~network of processing nodes. Each node performs measurement and estimation using the Kalman filtering technique, communicates its results to other nodes in the network, and utilizes similar results from the other nodes in its own computations. We assume that the connection graph of the network is not complete, i.e. not all nodes...
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Distributed state estimation using a network of asynchronous processing nodes
PublicationWe consider the problem of distributed state estimation of continuous-time stochastic processes using a~network of processing nodes. Each node performs measurement and estimation using the Kalman filtering technique, communicates its results to other nodes in the network, and utilizes similar results from the other nodes in its own computations. We assume that the connection graph of the network is not complete, i.e. not all nodes...
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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A method of the UMTS-FDD network design based on universal load characteristics
PublicationIn the paper an original method of the UMTS radio network design was presented. The method is based on simple way of capacity-coverage trade-off estimation for WCDMA/FDD radio interface. This trade-off is estimated by using universal load characteristics and normalized coverage characteristics. The characteristics are useful for any propagation environment as well as for any service performance requirements. The practical applications...
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Guessing Intrinsic Forwarding Trustworthiness of Wireless Ad Hoc Network Nodes
PublicationA novel node misbehavior detection system called GIFTED is proposed for a multihop wireless ad hoc network (WAHN) whose nodes may selfishly refuse to forward transit packets. The system guesses the nodes’ intrinsic forwarding trustworthiness (IFT) by analyzing end-to-end path performance rather than utilizing unreliable and incentive incompatible low-layer mechanisms. It can work with occasional IFT jumps, directional antennae,...
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Cellular network quality evaluation at a university campus on the eve of 5G
PublicationThanks to the availability of mobile devices and the spread of broadband access around the world, the number of network users continues to grow. This has raised user awareness when it comes to the quality of content they consume. Many service providers and operators focus on monitoring QoN (Quality of Network) and QoS (Quality of Service) parameters, particularly those influenced by bandwidth and latency. However, for most end-users,...
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Network-assisted processing of advanced IoT applications: challenges and proof-of-concept application
PublicationRecent advances in the area of the Internet of Things shows that devices are usually resource-constrained. To enable advanced applications on these devices, it is necessary to enhance their performance by leveraging external computing resources available in the network. This work presents a study of computational platforms to increase the performance of these devices based on the Mobile Cloud Computing (MCC) paradigm. The main...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Photovoltaic bulk heterojunctions with interpenetrating network based on semiconducting polymers
PublicationPhotovoltaic cells are supposed to be the most common generators of useful electricity in the nearest future as they utilize inexhaustible carriers of renewable energy called photons. Despite the fact that 95% of worldwide applied photovoltaic devices are based on inorganic semiconductors the area of organic photovoltaics grows successively due to possibility of considerable reduction of manufacturing costs. Since the Heeger's...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Sylwester Kaczmarek dr hab. inż.
PeopleSylwester Kaczmarek received his M.Sc in electronics engineering, Ph.D. and D.Sc. in switching and teletraffic science from the Gdansk University of Technology, Gdansk, Poland, in 1972, 1981 and 1994, respectively. His research interests include: IP QoS and GMPLS and SDN networks, switching, QoS routing, teletraffic, multimedia services and quality of services. Currently, his research is focused on developing and applicability...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Planning a Cost-Effective Delay-Constrained Passive Optical Network for 5G Fronthaul
PublicationWith the rapid growth in the telecommunications industry moving towards 5G and beyond (5GB) and the emergence of data-hungry and time-sensitive applications, Mobile Network Operators (MNOs) are faced with a considerable challenge to keep up with these new demands. Cloud radio access network (CRAN) has emerged as a cost-effective architecture that improves 5GB performance. The fronthaul segment of the CRAN necessitates a high-capacity...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Traffic Type Influence on Performance of OSPF QoS Routing
PublicationFeasibility studies with QoS routing proved that the network traffic type has influence on routing performance. In this work influence of self-similar traffic for network with DiffServ architecture and OSPF QoS routing has been verified. Analysis has been done for three traffic classes. Multiplexed ON-OFF model was used for self-similar traffic generation. Comparison of simulation results were presented using both relative and...
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Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.
PublicationCoordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Analytical Traffic Model for a Multidomain IMS/NGN Network Including Service and Transport Stratum
PublicationThis paper addresses the problem of modelling call processing performance (CPP) in a multidomain Next Generation Network (NGN) architecture including the elements of the IP Multimedia Subsystem (IMS) in service stratum and based on the Multiprotocol Label Switching (MPLS) technology in transport stratum. An analytical traffic model for such an architecture is proposed by integrating the formerly implemented submodels of service...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Development of Intelligent Control for Annealing Unit to Ensure the Minimization of Retroactive Effects on the Supply Network
PublicationResearch conducted by our team focused on the development of a complete annealing unit, using modern technologies and components, such as a programmable logic controller, an industrial computer and microcontrollers, ensuring an intelligent way to control power semiconductor elements (SSR relays), with regard to minimizing retroactive effects on the supply network. This modern configuration offers a number of new possibilities of...
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5G Millimeter Wave Network Optimization: Dual Connectivity and Power Allocation Strategy
PublicationThe fifth generation (5G) of mobile networks utilizing millimeter Wave (mmWave) bands can be considered the leading player in meeting the continuously increasing hunger of the end user demands in the near future. However, 5G networks are characterized by high power consumption, which poses a significant challenge to the efficient management of base stations (BSs) and user association. Implementing new power consumption and user...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublicationThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublicationIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...