Bilgisayar Mühendisliği Bölümü Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/45
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Article Citation - WoS: 15Citation - Scopus: 15Rapidly Time-Varying Channel Estimation for Full-Duplex Amplify-And One-Way Relay Networks(IEEE-INST Electrical Electronics Engineers Inc, 2018) Şenol, Habib; Li, Xiaofeng; Tepedelenlioglu, CihanEstimation of both cascaded and residual self-interference (RSI) channels and a new training frame structure are considered for full-duplex (FD) amplify-and-forward (AF) one-way relay networks with rapidly time-varying individual channels. To estimate the RSI and the rapidly time-varying cascaded channels we propose a new training frame structure in which orthogonal training blocks are sent by the source node and delivered to the destination over an FD-AF relay. Exploiting the orthogonality of the training blocks we obtain two decoupled training signal models for the estimation of the RSI and the cascaded channels. We apply linear minimum mean square error (MMSE) based estimators to the cascaded channel as well as RSI channel. In order to investigate the mean square error (MSE) performance of the system we also derive the Bayesian Cramer-Rao lower bound. As another performance benchmark we also assess the symbol error rate (SER) performances corresponding to the estimated and the perfect channel state information available at the receiver side. Computer simulations exhibit the proposed training frame structure and the linear MMSE estimator MSE and SER performances are shown.Article Optimizing Neuron Simulation Environment Using Remote Memory Access With Recursive Doubling on Distributed Memory Systems(Hindawi Ltd, 2016) Shehzad, Danish; Bozkuş, ZekiIncrease in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.Article Citation - WoS: 2Nonuniform Sampling for Detection of Abrupt Changes(Birkhauser Boston Inc, 2003) Kerestecioğlu, Feza; Tokat, SezaiIn this work detection of abrupt changes in continuous-time linear stochastic systems and selection of the sampling interval to improve the detection performance are considered. Cost functions are proposed to optimize both uniform and nonuniform sampling intervals for the well-known cumulative sum algorithm. Some iterative techniques are presented to make online optimization computationally feasible. It is shown that considerable improvement in the detection performance can be obtained by using nonuniform sampling intervals.Article Citation - WoS: 13Citation - Scopus: 21Improving Energy-Efficiency of Wsns Through Lefca(Sage Publications Inc, 2016) Cengiz, Korhan; Dağ, TamerWireless sensor networks (WSNs) have become an important part of our lives as they can be used in vast application areas from disaster relief to health care. As a consequence the life span and the energy consumption of a WSN have become a challenging research area. According to the existing studies instead of using direct transmission or multihop routing clustering can significantly reduce the energy consumption of sensor nodes and can prolong the lifetime of a WSN. In this paper we propose a low energy fixed clustering algorithm (LEFCA) for WSNs. With LEFCA the clusters are constructed during the set-up phase. A sensor node which becomes a member of a cluster stays in the same cluster throughout the life span of the network. LEFCA not only improves the lifetime of the network but also decreases the energy dissipation significantly.Conference Object Citation - WoS: 2Power Control and Resource Allocation in Tdd-Ofdm Based Femtocell Networks With Interference(IEEE, 2017) Altabbaa, Mhd Tahssin; Arsan, Taner; Panayırcı, ErdalFemtocell technology is a promising solution for different dilemmas in cellular networks. In femtocell power control the interference experienced by the network is divided into two main tiers according to the type of network whose signal is interfering with another network. In utilizing the functionality of a two-tier network where femtocell technology is deployed a major challenge is in sharing the frequency resource of a macrocell. This paper proposes an enhanced dynamic algorithm bounded by two constraints to optimize the transmission powers of femtocell users in TDD-OFDM based femtocell networks taking into consideration rate enhancement of femtocell mobile stations. We compare our algorithm with the macrocell guard system which allows femtocells to occupy only the subchannels unoccupied by the macrocell.Conference Object Citation - WoS: 4Performance Investigation of Ieee 802.11af Systems Under Realistic Channel Conditions(IEEE, 2015) Macit, Mustafa Can; Şenol, Habib; Erküçük, SerhatAs the analog TV broadcasting channels have become less frequently used in the last decade there has been a great interest in these frequency bands for the deployment of metropolitan local and personal area networks. Among them the local area network standard IEEE 802.11af defines PHY and MAC layer implementation of such networks in these unused frequency bands also named television white space (TVWS). According to the standard the systems may use contiguous or non-contiguous channels during their operation depending on the channel availability. In this paper we investigate in detail the performance of different operation modes of these systems under realistic channel conditions. While the perfect knowledge of channel would result in similar system performances as the number of in-between-bands occupying the non-contiguous modes is increased the channel estimation performance degrades drastically which is quantified in this study. In addition it is shown that determining the true locations of multipaths heavily relies on the selected channel resolution and has a significant effect on the system performance. Numerical examples are given to demonstrate the effects of both the non-contiguous operation modes and the selected channel resolution.Article Citation - WoS: 4Citation - Scopus: 6Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems(Springer, 2018) Özmen, Atilla; Şenol, HabibIn this paper channel estimation problem in a visible light communication system is considered. The information data is transmitted using asymmetrical clipped optical orthogonal frequency division multiplexing. Channel estimation and symbol detection are performed by the Maximum Likelihood and the Linear Minimum Mean Square Error detection techniques respectively. The system performance is investigated in realistic environment that is simulated using an indoor channel model. Two different channels are produced using the indoor channel model. Symbol error rate (SER) performance of the system with estimated channels is presented for QPSK and 16-QAM digital modulation types and compared with the perfect channel state information. As a mean square error (MSE) performance benchmark for the channel estimator Cramer-Rao lower bound is also derived. MSE and SER performances of the simulation results are presented.Conference Object Citation - WoS: 1An Analysis for the Use of Compressed Sensing Method in Microwave Imaging(IEEE, 2017) Yiğit, Enes; Tekbaş, Mustafa; Ünal, İlhami; Erdoğan, Sercan; Çalışkan, CaferOne of the most important problems encountered in microwave imaging methods is intensive data processing traffic that occurs when high resolution and real time tracking is desired. Radar signals can be recovered without loss of data with a randomly selected subset of the measurement data by compression sensing (CS) method which has been popular in recent years. For this reason, in this study, the use and capabilities of the CS method were investigated for tracking moving human, and the target information was correctly determined for the data obtained much below the Nyquist sampling criterion. In this study, it was revealed that the CS method can be developed for target detection and trackingArticle Citation - WoS: 1Citation - Scopus: 1Bayesian Estimation of Discrete-Time Cellular Neural Network Coefficients(TUBITAK Scientific & Technical Research Council Turkey, 2017) Özer, Hakan Metin; Özmen, Atilla; Şenol, HabibA new method for finding the network coefficients of a discrete-time cellular neural network (DTCNN) is proposed. This new method uses a probabilistic approach that itself uses Bayesian learning to estimate the network coefficients. A posterior probability density function (PDF) is composed using the likelihood and prior PDFs derived from the system model and prior information respectively. This posterior PDF is used to draw samples with the help of the Metropolis algorithm a special case of the Metropolis--Hastings algorithm where the proposal distribution function is symmetric and resulting samples are then averaged to find the minimum mean square error (MMSE) estimate of the network coefficients. A couple of image processing applications are performed using these estimated parameters and the results are compared with those of some well-known methods.Conference Object Frequency selective fading channel estimation in OFDM systems using KL expansion(2005) Şenol, Habib; Cirpan, Hakan Ali; Panayırcı, ErdalThis paper proposes a computationally efficient linear minimum mean square error (MMSE) channel estimation algorithm based on KL series expansion for OFDM systems. Based on such expansion no matrix inversion is required in the proposed MMSE estimator. Moreover truncation in the linear expansion of channel is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We provide performance analysis results studying the influence of the effect of SNR and correlation mismatch on the estimator performance. Simulation results confirm our theoretical results and illustrate that the proposed algorithm is capable of tracking fast fading and improving performance.Article Citation - WoS: 1Citation - Scopus: 2A Bayesian Approach To Developing a Strategic Early Warning System for the French Milk Market(Halmstad University, 2017) Bisson, Christophe; Gürpınar, FurkanA new approach is provided in our paper for creating a strategic early warning system allowing the estimation of the future state of the milk market as scenarios. This is in line with the recent call from the EU commission for tools that help to better address such a highly volatile market. We applied different multivariate time series regression and Bayesian networks on a pre-determined map of relations between macro-economic indicators. The evaluation of our findings with root mean square error (RMSE) performance score enhances the robustness of the prediction model constructed. Our model could be used by competitive intelligence teams to obtain sharper scenarios, leading companies and public organisations to better anticipate market changes and make more robust decisions.Article Citation - WoS: 27Citation - Scopus: 27Exploiting Heterogeneous Parallelism With the Heterogeneous Programming Library(Academic Press Inc Elsevier Science, 2013) Vinas, Moises; Bozkuş, Zeki; Fraguela, Basilio B.While recognition of the advantages of heterogeneous computing is steadily growing the issues of programmability and portability hinder its exploitation. The introduction of the OpenCL standard was a major step forward in that it provides code portability but its interface is even more complex than that of other approaches. In this paper we present the Heterogeneous Programming Library (HPL) which permits the development of heterogeneous applications addressing both portability and programmability while not sacrificing high performance. This is achieved by means of an embedded language and data types provided by the library with which generic computations to be run in heterogeneous devices can be expressed. A comparison in terms of programmability and performance with OpenCL shows that both approaches offer very similar performance while outlining the programmability advantages of HPL. (C) 2013 Elsevier Inc. All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 4Distributed Estimation Over Parallel Fading Channels With Channel Estimation Error(IEEE, 2008) Şenol, Habib; Tepedelenlioğlu, CihanWe consider distributed estimation of a source observed by sensors in additive Gaussian noise where the sensors are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. We adopt a two-phase approach of (i) channel estimation with training and (ii) source estimation given the channel estimates where the total power is fixed. We prove that allocating half the total power into training is optimal and show that compared to the perfect channel case a performance loss of at least 6 dB is incurred. In addition we show that unlike the perfect channel case increasing the number of sensors will lead to an eventual degradation in performance. We characterize the optimum number of sensors as a function of the total power and noise statistics. Simulations corroborate our analytical findings.Article Citation - WoS: 9Citation - Scopus: 11Leveraging Saving-Based Algorithms by Master-Slave Genetic Algorithms(Pergamon-Elsevier Science Ltd, 2011) Battarra, Maria; Benedettini, Stefano; Roli, AndreaSaving-based algorithms are commonly used as inner mechanisms of efficient heuristic construction procedures. We present a general mechanism for enhancing the effectiveness of such heuristics based on a two-level genetic algorithm. The higher-level algorithm searches in the space of possible merge lists which are then used by the lower-level saving-based algorithm to build the solution. We describe the general framework and we illustrate its application to three hard combinatorial problems. Experimental results on three hard combinatorial optimization problems show that the approach is very effective and it enables considerable enhancement of the performance of saving-based algorithms. (C) 2011 Elsevier Ltd. All rights reserved.Article New Generation Android Operating System-Basedmobile Application: Rss/News Reader(Springer Verlag, 2015) Arsan, Taner; Erşahin, Mehmet Arif; Alp, EbruRSS (Rich Site Summary)/News Reader is a web-based Android OS application developed by using PhoneGap framework. HTML5 CSS and JavaScript are basically used for implementation instead of native Android programming language. This application has a production process like a web application because it is actually a fully working web program which is wrapped by PhoneGap framework. This means the application could be used on almost every mobile platform with making some basic arrangements.RSS/News Reader mobile application takes advantage of both flexibility of web design and built-in features of the device it is installed. This combination provides a complete mobile application which eliminates the need to use different native languages with its hybrid form. This hybrid structure makes mobile programming faster and easier to implement.In this new generation operating system-based mobile application a combination of PhoneGap framework HTML5 CSS3 JavaScript jQuery Mobile Python and Django is used for implementation. © Springer International Publishing Switzerland 2015.Conference Object Citation - Scopus: 2Active Reconfigurable Control of a Submarine With Indirect Adaptive Control(2003) Demirci, Ufuk; Kerestecioğlu, FezaAn indirect adaptive controller is designed for submersibles. The design is developed using a linearized MIMO model of a submarine. Standard recursive least squares estimation method is used to estimate the parameters. Depth and pitch angle of the submarine is controlled by means of the well-known indirect self-tuning method. In case of a system fault estimated parameters of the submarine model have been used to update the controller coefficients.Article Citation - WoS: 3Citation - Scopus: 3Transmitter Source Location Estimation Using Crowd Data(Pergamon-Elsevier Science Ltd, 2018) Öğrenci, Arif Selçuk; Arsan, TanerThe problem of transmitter source localization in a dense urban area has been investigated where a supervised learning approach utilizing neural networks has been adopted. The cellular phone network cells and signals have been used as the test bed where data are collected by means of a smart phone. Location and signal strength data are obtained by random navigation and this information is used to develop a learning system for cells with known base station location. The model is applied to data collected in other cells to predict their base station locations. Results are consistent and indicating a potential for effective use of this methodology. The performance increases by increasing the training set size. Several shortcomings and future research topics are discussed. (C) 2017 Elsevier Ltd. All rights reserved.Conference Object Citation - Scopus: 4Pilot-Aided Bayesian Mmse Channel Estimation for Ofdm Systems: Algorithm and Performance Analysis(2004) Şenol, Habib; Cirpan, Hakan Ali; Panayırcı, ErdalThis paper proposes a computationally efficient pilot-aided minimum mean square error (MMSE) channel estimation algorithm for OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates uncorrelated series expansion coefficients. Moreover optimal rank reduction is achieved in the proposed approach by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first consider the stochastic Cramer-Rao bound and derive the closed-form expression for the random KL coefficients. We then exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. © 2004 IEEE.Article Citation - WoS: 1Citation - Scopus: 1Hybrid Mpi Plus Upc Parallel Programming Paradigm on an Smp Cluster(TUBITAK Scientific & Technical Research Council Turkey, 2012) Bozkuş, ZekiThe symmetric multiprocessing (SMP) cluster system which consists of shared memory nodes with several multicore central processing units connected to a high-speed network to form a distributed memory system is the most widely available hardware architecture for the high-performance computing community. Today the Message Passing Interface (MPI) is the most widely used parallel programming paradigm for SMP clusters in which the MPI provides programming both for an SMP node and among nodes simultaneously. However Unified Parallel C (UPC) is an emerging alternative that supports the partitioned global address space model that can be again employed within and across the nodes of a cluster. In this paper we describe a hybrid parallel programming paradigm that was designed to combine MPI and UPC programming models. This paradigm's objective is to mix the MPI's data locality control and scalability strengths with UPC's fine-grain parallelism and ease of programming to achieve multiple-level parallelism at the SMP cluster which itself has multilevel parallel architecture. Utilizing a proposed hybrid model and comparing MPI-only to UPC-only implementations this paper presents a detailed description of Cannon's algorithm benchmark application with performance results of a random-access benchmark and the Barnes-Hut N-Body simulation. Experiments indicate that the hybrid MPI+UPC model can significantly provide performance increases of up to double in comparison with UPC-only implementation and up to 20% increases in comparison to MPI-only implementation. Furthermore an optimization was achieved that improved the hybrid performance by an additional 20%.Article Citation - WoS: 1Citation - Scopus: 1The Effects of Higher-Order Approximations in a Fluid-Filled Elastic Tube With Stenosis(Verlag der Zeitschrift fur Naturforschung, 2006) Demiray, HilmiTreating arteries as thin-walled prestressed elastic tubes with a narrowing (stenosis) and blood as an inviscid fluid we study the propagation of weakly nonlinear waves in such a fluid-filled elastic tube by employing the reductive perturbation method in the long wave approximation. It is shown that the evolution equation of the first-order term in the perturbation expansion may be described by the conventional Korteweg-de Vries (KdV) equation. The evolution equation for the second-order term is found to be the linearized KdV equation with a nonhomogeneous term which contains the contribution of the stenosis. A progressive wave type solution is sought for the evolution equation and it is observed that the wave speed is variable which results from the stenosis. We study the variation of the wave speed with the distance parameter ? for various amplitude values of the stenosis. It is observed that near the center of the stenosis the wave speed decreases with increasing stenosis amplitude. However sufficiently far from the center of the stenosis stenosis amplitude becomes negligibly small. © 2006 Verlag der Zeitschrift für Naturforschung.
