Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/45

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Citation - WoS: 15
Citation - Scopus: 15
Rapidly 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, Cihan
Estimation 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.
Optimizing Neuron Simulation Environment Using Remote Memory Access With Recursive Doubling on Distributed Memory Systems
(Hindawi Ltd, 2016) Shehzad, Danish; Bozkuş, Zeki
Increase 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.
Citation - WoS: 2
Nonuniform Sampling for Detection of Abrupt Changes
(Birkhauser Boston Inc, 2003) Kerestecioğlu, Feza; Tokat, Sezai
In 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.
Citation - WoS: 13
Citation - Scopus: 21
Improving Energy-Efficiency of Wsns Through Lefca
(Sage Publications Inc, 2016) Cengiz, Korhan; Dağ, Tamer
Wireless 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.
Citation - WoS: 1
Citation - Scopus: 1
Accelerating Brain Simulations on Graphical Processing Units
(IEEE, 2015) Kayraklıoğlu, Engin; El-Ghazawi, Tarek A.; Bozkuş, Zeki
NEural Simulation Tool(NEST) is a large scale spiking neuronal network simulator of the brain. In this work we present a CUDA(R) implementation of NEST. We were able to gain a speedup of factor 20 for the computational parts of NEST execution using a different data structure than NEST's default. Our partial implementation shows the potential gains and limitations of such possible port. We discuss possible novel approaches to be able to adapt generic spiking neural network simulators such as NEST to run on commodity or high-end GPGPUs.
Citation - WoS: 1
Citation - Scopus: 1
Partitioning 3-Arcs Into Steiner Triple Systems
(Wiley, 2017) Çalışkan, Cafer
In this article it is shown that there is a partitioning of the set of 3-arcs in a projective plane of order three into nine pairwise disjoint Steiner triple systems of order 13.
Fully Decentralized, Collaborative Multilateration Primitives for Uniquely Localizing Wsns
(Springer, 2009) Cakiroglu, Arda; Erten, Cesim
We provide primitives for uniquely localizing WSN nodes. The goal is to maximize the number of uniquely localized nodes assuming a fully decentralized model of computation. Each node constructs a cluster of its own and applies unique localization primitives on it. These primitives are based on constructing a special order for multilaterating the nodes within the cluster. The proposed primitives are fully collaborative and thus the number of iterations required to compute the localization is fewer than that of the conventional iterative multilateration approaches. This further limits the messaging requirements. With relatively small clusters and iteration counts we can localize almost all the uniquely localizable nodes. © 2009 Springer Berlin Heidelberg.
Citation - WoS: 2
Power Control and Resource Allocation in Tdd-Ofdm Based Femtocell Networks With Interference
(IEEE, 2017) Altabbaa, Mhd Tahssin; Arsan, Taner; Panayırcı, Erdal
Femtocell 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.
Citation - WoS: 4
Performance Investigation of Ieee 802.11af Systems Under Realistic Channel Conditions
(IEEE, 2015) Macit, Mustafa Can; Şenol, Habib; Erküçük, Serhat
As 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.
Citation - WoS: 18
Citation - Scopus: 18
Modeling the Optical Properties of Wo(3) and Wo(3)-Sio(2) Thin Films
(Elsevier Science Bv, 2008) Saygin-Hinczewski, Dursen; Hinczewski, Michael; Sorar, İdris; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
The optical properties and surface morphology of sol-gel spin coated WO(3) and WO(3)-SiO(2) composite films annealed at 250 and 400 degrees C are investigated. For the purpose of extracting the optical parameters of the films a novel form for the dielectric function is introduced consisting of two Tauc-Lorentz oscillators and an Urbach tail component which is suited for amorphous multi-transition materials with substantial subgap absorption. The evolution of the refractive indices transmittances and band gaps with doping is marked by sizable shifts at 2.0-2.5% SiO(2) doping for the 250 degrees C films and 4.0-4.5% doping for the 400 degrees C films. In addition pronounced changes in the surface roughness of the films occur at these doping values. (c) 2008 Elsevier B.V. All rights reserved.
Machine Learning Approaches for Predicting Protein Complex Similarity
(Mary Ann Liebert Inc Publ, 2017) Farhoodi, Roshanak; Akbal-Delibas, Bahar; Haspel, Nurit
Discriminating native-like structures from false positives with high accuracy is one of the biggest challenges in protein-protein docking. While there is an agreement on the existence of a relationship between various favorable intermolecular interactions (e.g. Van der Waals electrostatic and desolvation forces) and the similarity of a conformation to its native structure the precise nature of this relationship is not known. Existing protein-protein docking methods typically formulate this relationship as a weighted sum of selected terms and calibrate their weights by using a training set to evaluate and rank candidate complexes. Despite improvements in the predictive power of recent docking methods producing a large number of false positives by even state-of-the-art methods often leads to failure in predicting the correct binding of many complexes. With the aid of machine learning methods we tested several approaches that not only rank candidate structures relative to each other but also predict how similar each candidate is to the native conformation. We trained a two-layer neural network a multilayer neural network and a network of Restricted Boltzmann Machines against extensive data sets of unbound complexes generated by RosettaDock and PyDock. We validated these methods with a set of refinement candidate structures. We were able to predict the root mean squared deviations (RMSDs) of protein complexes with a very small often less than 1.5 angstrom error margin when trained with structures that have RMSD values of up to 7 angstrom. In our most recent experiments with the protein samples having RMSD values up to 27 angstrom the average prediction error was still relatively small attesting to the potential of our approach in predicting the correct binding of protein-protein complexes.
Effect of Inter-Block Region on Compressed Sensing Based Channel Estimation in Tds-Ofdm Systems
(IEEE, 2016) Başaran, Mehmet; Erküçük, Serhat; Şenol, Habib; Cirpan, Hakan Ali
Time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) is the basis technology for digital television standard (DTV) employed in some countries thanks to its high spectral efficiency when compared to traditional cyclic prefix OFDM. Moreover it does not require pilot usage in frequency domain channel estimation. Instead of data usage as cyclic prefix pseudo-noise (PN) sequences are transmitted in guard intervals. Due to interference from the previous OFDM data symbol the received signal in guard interval can be decomposed into a small-sized signal that contains only PN sequences utilizing the inter-block-interference (IBI)-free region in the convolution matrix. Due to sparsity multipath fading channel can be obtained by the application of compressed sensing (CS) technique to reconstruct the high-dimensional sparse channel from the decreased-size of received signal through the known PN sequence matrix. In this study the effect of the size of IBI-free region on CS and Bayesian CS (BCS) based channel estimation is investigated. Accordingly reconstruction error performances of basis pursuit (BP) and BCS are compared. Simulation results show that the channel estimation can be improved by trading-off the length of the IBI-free region. However an increase in IBI-free region leads to decreased energy efficiency at both the transmitter and receiver side.
Citation - WoS: 11
Citation - Scopus: 10
Early Steps in Automated Behavior Mapping via Indoor Sensors
(MDPI, 2017) Arsan, Taner; Kepez, Orçun
Behavior mapping (BM) is a spatial data collection technique in which the locational and behavioral information of a user is noted on a plan layout of the studied environment. Among many indoor positioning technologies we chose Wi-Fi BLE beacon and ultra-wide band (UWB) sensor technologies for their popularity and investigated their applicability in BM. We tested three technologies for error ranges and found an average error of 1.39 m for Wi-Fi in a 36 m(2) test area (6m x 6 m) 0.86 m for the BLE beacon in a 37.44 m(2) test area (9.6 m x 3.9 m) and 0.24 m for ultra-wide band sensors in a 36 m(2) test area (6 m x 6 m). We simulated the applicability of these error ranges for real-time locations by using a behavioral dataset collected from an active learning classroom. We used two UWB tags simultaneously by incorporating a custom-designed ceiling system in a new 39.76 m(2) test area (7.35 m x 5.41 m). We considered 26 observation points and collected data for 180 s for each point (total 4680) with an average error of 0.2072 m for 23 points inside the test area. Finally we demonstrated the use of ultra-wide band sensor technology for BM.
Citation - WoS: 3
Performance Improvement of Threshold Based Audio Steganography Using Parallel Computation
(Science & Information SAI Organization Ltd, 2016) Shoaib, Muhammad; Shehzad, Danish; Umar, Arif Iqbal; Khan, Zakir; Dağ, Tamer; Ul Amin, Noor
Audio steganography is used to hide secret information inside audio signal for the secure and reliable transfer of information. Various steganography techniques have been proposed and implemented to ensure adequate security level. The existing techniques either focus on the payload or security but none of them has ensured both security and payload at same time. Data Dependency in existing solution was reluctant for the execution of steganography mechanism serially. The audio data and secret data pre-processing were done and existing techniques were experimentally tested in Matlab that ensured the existence of problem in efficient execution. The efficient least significant bit steganography scheme removed the pipelining hazard and calculated Steganography parallel on distributed memory systems. This scheme ensures security focuses on payload along with provisioning of efficient solution. The result depicts that it not only ensures adequate security level but also provides better and efficient solution.
Citation - WoS: 9
Citation - Scopus: 11
Leveraging Saving-Based Algorithms by Master-Slave Genetic Algorithms
(Pergamon-Elsevier Science Ltd, 2011) Battarra, Maria; Benedettini, Stefano; Roli, Andrea
Saving-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.
Max-Pivot Routing for Opportunistic Networks
(2013) Dağ, Tamer
Opportunistic networks are challenging types of networks where network connections are imminent. Network topologies are dynamic and can rapidly change. A path between a source node and a destination node may or may not exist the network can be disconnected. This type of behavior observed under opportunistic networks makes classical networking solutions impractical. Thus traditional routing algorithms are not suitable for such networks and will not be useful. Although flooding might be seen as the best solution to reach a destination under opportunistic networks flooding solutions' extensive usage of network resources is an extreme overhead. In this paper max- pivot routing for opportunistic networks is proposed and described. With max-pivot routing it is observed that the induced network traffic is significantly reduced while still achieving the benefits of a flooding based routing. The performance comparisons of max-pivot routing and flooding based routing methods show that max-pivot routing can be a successful routing method for opportunistic networks.
Citation - WoS: 4
Citation - Scopus: 6
Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems
(Springer, 2018) Özmen, Atilla; Şenol, Habib
In 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.
Citation - WoS: 1
An Analysis for the Use of Compressed Sensing Method in Microwave Imaging
(IEEE, 2017) Yiğit, Enes; Tekbaş, Mustafa; Ünal, İlhami; Erdoğan, Sercan; Çalışkan, Cafer
One 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 tracking
Citation - WoS: 1
Citation - Scopus: 1
Bayesian Estimation of Discrete-Time Cellular Neural Network Coefficients
(TUBITAK Scientific & Technical Research Council Turkey, 2017) Özer, Hakan Metin; Özmen, Atilla; Şenol, Habib
A 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.
Citation - Scopus: 4
Pilot-Aided Bayesian Mmse Channel Estimation for Ofdm Systems: Algorithm and Performance Analysis
(2004) Şenol, Habib; Cirpan, Hakan Ali; Panayırcı, Erdal
This 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.

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