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.
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 - WoS: 64
Citation - Scopus: 89
Energy Aware Multi-Hop Routing Protocol for Wsns
(IEEE, 2018) Cengiz, Korhan; Dağ, Tamer
In this paper we propose an energy-efficient multi-hop routing protocol for wireless sensor networks (WSNs). The nature of sensor nodes with limited batteries and inefficient protocols are the key limiting factors of the sensor network lifetime. We aim to provide for a green routing protocol that can be implemented in a wireless sensor network. Our proposed protocol's most significant achievement is the reduction of the excessive overhead typically seen in most of the routing protocols by employing fixed clustering and reducing the number of cluster head changes. The performance analysis indicates that overhead reduction significantly improves the lifetime as energy consumption in the sensor nodes can be reduced through an energy-efficient protocol. In addition the implementation of the relay nodes allows the transmission of collected cluster data through inter cluster transmissions. As a result the scalability of a wireless sensor network can be increased. The usage of relay nodes also has a positive impact on the energy dissipation in the network.
Citation - Scopus: 1
Semiblind Joint Channel Estimation and Equalization for Ofdm Systems in Rapidly Varying Channels
(2010) Şenol, Habib; Panayırcı, Erdal; Poor, H. Vincent; Oğuz, Onur; Vandendorpe, Luc
We describe a new joint iterative channel estimation and equalization algorithm for joint channel estimation and data detection for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and rapidly timevarying channels. The algorithm is based on the expectation maximization-maximum a posteriori (EM-MAP) technique which is very suitable for the multicarrier signal formats. The algorithm leads to a receiver structure that yields the equalized output using the channel estimates. The pilot symbols are employed to estimate the initial channel coefficients effectively and unknown data symbols are averaged out in the algorithm. The band-limited discrete cosine serial expansion of low dimensionality is employed to represent the time-varying fading channel. In this way the resulting reduced dimensional channel coefficients are estimated iteratively with tractable complexity. The extensive computer simulations show that the algorithm has excellent symbol error rate (SER) and mean square error (MSE) performances for very high mobility even during the initialization step. Copyright © ?enol et. al.
Citation - WoS: 1
Citation - Scopus: 1
A Framework for Combined Recognition of Actions and Objects
(Springer-Verlag Berlin, 2012) Ar, İlktan; Akgül, Yusuf Sinan
This paper proposes a novel approach to recognize actions and objects within the context of each other. Assuming that the different actions involve different objects in image sequences and there is one-to-one relation between object and action type we present a Bayesian network based framework which combines motion patterns and object usage information to recognize actions/objects. More specifically our approach recognizes high-level actions and the related objects without any body-part segmentation hand tracking and temporal segmentation methods. Additionally we present a novel motion representation based on 3D Haar-like features which can be formed by depth color or both images. Our approach is also appropriate for object and action recognition where the involved object is partially or fully occluded. Finally experiments show that our approach improves the accuracy of both action and object recognition significantly.
Citation - WoS: 8
Citation - Scopus: 10
Rednemo: Topology-Based Ppi Network Reconstruction Via Repeated Diffusion With Neighborhood Modifications
(Oxford University Press, 2017) Alkan, Ferhat; Erten, Cesim
Motivation: Analysis of protein-protein interaction (PPI) networks provides invaluable insight into several systems biology problems. High-throughput experimental techniques together with computational methods provide large-scale PPI networks. However a major issue with these networks is their erroneous nature
Citation - Scopus: 1
An Analysis For The Use Of Compressed Sensing Method İn Microwave İmaging [mikrodalga Görüntülemede Sıkıştırılmış Algılama Yönteminin Kullanımına Yönelik Bir Analiz]
(Institute of Electrical and Electronics Engineers Inc., 2017) Yiğit, Enes; Tekbaş, Mustafa; Ünal, İlhami; Erdogan, 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. © 2017 IEEE.
Citation - Scopus: 1
Extending the Lifetime of Wsns With Maximum Energy Selection Algorithm (mesa)
(Institute of Electrical and Electronics Engineers Inc., 2017) Cengiz, Korhan; Dağ, Tamer
The limited battery supply of a sensor node is one of the most important factors that limit the lifetime of the WSNs. As a consequence increasing the lifetime of WSNs through energy efficient mechanisms has become a challenging research area. Previous studies have shown that instead of implementing direct transmission or multi-hop routing clustering can significantly improve the total energy dissipation and lifetime of a WSN. The traditional LEACH and LEACH based algorithms have evolved from this idea. In this paper we propose a fixed clustering routing algorithm for WSNs which selects the node with maximum residual energy for the following rounds according to a threshold level. The Maximum Energy Selection Algorithm (MESA) can improve the lifetime of the network and reduce the energy dissipation significantly. Our studies have shown that when compared with LEACH and LEACH based algorithms such as ModLEACH and DEEC MESA gains for the lifetime extension and energy dissipation is very important. © 2016 IEEE.
Citation - WoS: 9
Citation - Scopus: 9
Navigation of Non-Communicating Autonomous Mobile Robots With Guaranteed Connectivity
(Cambridge Univ Press, 2013) Cezayirli, Ahmet; Kerestecioğlu, Feza
We consider the connectivity of autonomous mobile robots. The robots navigate using simple local steering rules without requiring explicit communication among themselves. We show that using only position information of neighbors the group connectivity can be sustained even in the case of bounded position measurement errors and the occlusion of robots by other robots in the group. In implementing the proposed scheme sub-optimal solutions are invoked to avoid an excessive computational burden. We also discuss the possibility of deadlock which may bring the group to a standstill and show that the proposed methodology avoids such a scenario in real-life settings.

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