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: 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: 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.
Citation - WoS: 1
Citation - Scopus: 1
Hybrid Mpi Plus Upc Parallel Programming Paradigm on an Smp Cluster
(TUBITAK Scientific & Technical Research Council Turkey, 2012) Bozkuş, Zeki
The 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%.
Citation - WoS: 18
Citation - Scopus: 23
Review of Bandwidth Estimation Tools and Application To Bandwidth Adaptive Video Streaming
(IEEE, 2012) Arsan, Taner
Streaming video is very popular in today's best effort delivery networks. Streaming video applications should not only have a good end-to-end transport performance but also have a Quality of Service (QoS) provisioning in network infrastructure. Bandwidth estimation schemes have been used to improve the QoS of multimedia services and video streaming applications. To ensure the video streaming service quality some other components such as adaptive rate allocation and control should be taken into consideration. This paper gives a review of bandwidth estimation tools for wired and wireless networks and then introduces a new bandwidth adaptive architecture for video streaming. © 2012 IEEE.
Joint Phase Noise Estimation And Source Detection [ortak Faz Gürültüsü Kestirimi ve Kaynak Sezimlemesi]
(2010) Kaleli, Burç Arslan; Şenol, Habib; Panayırcı, Erdal
Rapidly time-varying and random disturbing effects on the phase of a signal waveform are known as phase noise. In this paper we consider the problem of joint detection of continuous-valued information source output and estimation of a phase noise by using expectation maximization (EM) algorithm. In order to estimate phase noise initial phase noise values are determined by cubic interpolation that utilizes pilot symbols. Computer simulations are performed for the proposed algorithm and the average mean square error (MSE) - signal to noise ratio (SNR) performance of source detector and phase noise estimator is presented for each iteration of the algorithm. Moreover average MSE - pilot spacing performance curves of phase noise estimator are given for various SNR values. ©2010 IEEE.
Citation - Scopus: 3
First Impressions on Social Network Sites: Impact of Self-Disclosure Breadth on Attraction
(Academic Conferences and Publishing International Limited, 2017) Baruh, Lemi; Cemacılar, Zeynep; Bisson, Christophe; Chisik, Yoram I.
This paper reports the results of two experiments that investigate the relationship between the quantity of information disclosed on an SNS profile and profile viewers' first impressions of the profile owner. Both experiments utilized a 2 (low quantity of information vs. high quantity of information) by 2 (male vs. female profile) design. In the first experiment (n = 1059), the respondents were randomly assigned to the experimental conditions. The results showed that profile viewers were more favorable to profiles of women. Also, both for female and male SNS profiles, higher quantity of information led to more positive ratings of the profile owner. The second experiment expanded the findings from the first experiment in two ways. First, in the second experiment (n = 320), rather than being randomly assigned to the profile gender condition, the respondents could pick the gender of the profile they would review. Second, informed by previous research on face to face interactions which indicate that quantity of self-disclosure can increase interpersonal attraction by reducing the level of uncertainty about relational outcomes, we tested whether uncertainty reduction mediated the relationship between quantity of information presented in an SNS profile and interpersonal attraction. Female profiles were selected more often than male profiles by both female and male respondents; however, there was no difference in interpersonal attraction ratings that male and female profiles received. Higher quantity of information presented in an SNS profile had a significant impact on interpersonal attraction. The results from the second experiment also indicated that while quantity of information positively influenced profile viewers' perceptions regarding the agreeableness of the profile owner, it did not have an impact on viewers' perceptions regarding the dependability of the profile owner. As predicted, the impact of quantity of information on interpersonal attraction was mediated by a reduction in uncertainty levels.
Citation - WoS: 4
Citation - Scopus: 6
A Low-Complexity Time-Domain Mmse Channel Estimator for Space-time/Frequency Block-Coded Ofdm Systems
(Hindawi Publishing Corporation, 2006) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, Erdal
Focusing on transmit diversity orthogonal frequency-division multiplexing (OFDM) transmission through frequency-selective channels this paper pursues a channel estimation approach in time domain for both space-frequency OFDM (SF-OFDM) and space-time OFDM (ST-OFDM) systems based on AR channel modelling. The paper proposes a computationally efficient pilot-aided linear minimum mean-square-error (MMSE) time-domain channel estimation algorithm for OFDM systems with transmitter diversity in unknown wireless fading channels. The proposed approach employs a convenient representation of the channel impulse responses based on the Karhunen-Loeve (KL) orthogonal expansion and finds MMSE estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion no matrix inversion is required in the proposed MMSE estimator. Subsequently optimal rank reduction is applied to obtain significant taps resulting in a smaller computational load on the proposed estimation algorithm. The performance of the proposed approach is studied through the analytical results and computer simulations. In order to explore the performance the closed-form expression for the average symbol error rate (SER) probability is derived for the maximum ratio receive combiner (MRRC). We then consider the stochastic Cramer-Rao lower bound(CRLB) and derive the closed-form expression for the random KL coefficients and consequently exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. We also analyze the effect of a modelling mismatch on the estimator performance. Simulation results confirm our theoretical analysis and illustrate that the proposed algorithms are capable of tracking fast fading and improving overall performance. Copyright (C) 2006 Hindawi Publishing Corporation. All rights reserved.
Citation - WoS: 14
Force-Directed Approaches To Sensor Localization
(Association for Computing Machinery, 2010) Efrat, Alon; Forrester, David; Iyer, Anand; Kobourov, Stephen G.; Erten, Cesim; Kılış, Ozan
As the number of applications of sensor networks increases so does the interest in sensor network localization that is in recovering the correct position of each node in a network of sensors from partial connectivity information such as adjacency range or angle between neighboring nodes. In this article we consider the anchor-free localization problem in sensor networks that report possibly noisy range information and angular information about the relative order of each sensor's neighbors. Previously proposed techniques seem to successfully reconstruct the original positions of the nodes for relatively small networks with nodes distributed in simple regions. However these techniques do not scale well with network size and yield poor results with nonconvex or nonsimple underlying topology. Moreover the distributed nature of the problem makes some of the centralized techniques inapplicable in distributed settings. To address these problems we describe a multiscale dead-reckoning (MSDR) algorithm that scales well for large networks can reconstruct complex underlying topologies and is resilient to noise. The MSDR algorithm takes its roots from classic force-directed graph layout computation techniques. These techniques are augmented with a multiscale extension to handle the scalability issue and with a dead-reckoning extension to overcome the problems arising with nonsimple topologies. Furthermore we show that the distributed version of the MSDR algorithm performs as well as if not better than its centralized counterpart as shown by the quality of the layout measured in terms of the accuracy of the computed pairwise distances between sensors in the network.
Citation - Scopus: 1
A Synthesis Tool for the Multiplierless Realization of Fir-Based Multirate Dsp Systems
(IEEE, 2000) Yurdakul, Arda
In this study a synthesis tool using a novel multirate folding technique which handles each FIR filter in a multirate DSP system as a single node is developed. A new architecture is presented for the multiplierless realization of a fold of multirate FIR filters. This synthesizer fully exploits the redundancies (i.e. `idle' and `missing' cycles) and common terms in multirate systems without sacrificing from overall system quality to produce multiplierless multirate systems. It also enables the usage of a single clock for all parts of the circuit.
Citation - WoS: 1
Citation - Scopus: 5
Optimizing Neuron Brain Simulator With Remote Memory Access on Distributed Memory Systems
(Institute of Electrical and Electronics Engineers Inc., 2016) Shehzad, Danish; Bozkuş, Zeki
The Complex neuronal network models require support from simulation environment for efficient network simulations. To compute the models increasing complexity necessitated the efforts to parallelize the NEURON simulation environment. The computational neuroscientists have extended NEURON by dividing the equations for its subnet among multiple processors for increasing the competence of hardware. For spiking neuronal networks inter-processor spikes exchange consume significant portion of overall simulation time on parallel machines. In NEURON Message Passing Interface (MPI) is used for inter processor spikes exchange MPI-Allgather collective operation is used for spikes exchange generated after each interval across distributed memory systems. However as the number of processors become larger and larger MPI-Allgather method become bottleneck and needs efficient exchange method to reduce the spike exchange time. This work has improved MPI-Allgather method to Remote Memory Access (RMA) based on MPI-3.0 for NEURON simulation environment MPI based on RMA provides significant advantages through increased communication concurrency in consequence enhances efficiency of NEURON and scaling the overall run time for the simulation of large network models.1 © 2015 IEEE.
Citation - Scopus: 5
Fast Multi-View Face Trackingwith Pose Estimation
(2008) Meynet, Julien; Arsan, Taner; Mota, Javier Cruz; Thiran, Jean-Philippe Philippe H.
In this paper a fast and an effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose we employ a tree of boosted classifiers built using either Haar-like filters or Gauss filters. A first classifier extracts faces of any pose from the background. Then more specific classifiers discriminate between different poses. The tree of classifiers is trained by hierarchically sub-sampling the pose space. Finally Condensation algorithm is used for tracking the faces. Experiments show large improvements in terms of detection rate and processing speed compared to state-of-the-art algorithms.
Audience Tracking and Cheering Content Control in Sports Events
(IEEE, 2020) Yeşilyurt, Gözdenur; Dursun, Sefa; Kumas, Osman; Çakir, Nagehan; Arsan, Taner
Swearing cheers encountered in sports competitions do not comply with sports ethics and morals. Even if this kind of cheering is a group, the entire tribune block is penalized in accordance with the current rules. This method is not preventive and individual punishment should be used. The aim of this study is to determine the individuals who cheer with swearing content. In this study, the person detection is made with the multi-task cascaded convolutional neural network. Moreover, facial landmarks representing the facial regions and the regions related to them are determined as a result of this process. The mouth region is also determined by means of these important points removed, and finally the mouth is determined according to the equation. The face recognition is carried out because the person would be in a state of yelling if the mouth opening ratio exceeds the threshold value by determining the rate of opening. Landmarks extracted from the facial regions for the face recognition are transformed into feature vectors by FaceNet, and the model is created by classifying these vectors with classifiers to use in recognition process. When evaluated in terms of industry, face recognition and detection systems find a wide field of study.

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