Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/47

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Citation Count: 0
Amplitude and Frequency Modulations with Cellular Neural Networks
(Springer, 2015) Tander, Baran; Özmen, Atilla
Amplitude and frequency modulations are still the most popular modulation techniques in data transmission at telecommunication systems such as radio and television broadcasting gsm etc. However the architectures of these individual systems are totally different. In this paper it is shown that a cellular neural network with an opposite-sign template can behave either as an amplitude or a frequency modulator. Firstly a brief information about these networks is given and then the amplitude and frequency surfaces of the generated quasi-sine oscillations are sketched with respect to various values of their cloning templates. Secondly it is proved that any of these types of modulations can be performed by only varying the template components without ever changing their structure. Finally a circuit is designed simulations are presented and performance of the proposed system is evaluated. The main contribution of this work is to show that both amplitude and frequency modulations can be realized under the same architecture with a simple technique specifically by treating the input signals as template components.
Citation Count: 5
Analysis of Mixed-Element Structures Formed With Shunt Capacitors Separated by Transmission Lines
(IEEE-Inst Electrical Electronics Engineers Inc, 2019) Şengül, Metin Y.; Çakmak, Gökhan
In this brief, the analysis of mixed-element structures formed with shunt capacitors separated by commensurate transmission lines is performed first time in the literature. First, a low-pass lumped-element ladder network is considered. Then the series inductors are replaced with commensurate transmission lines. As a result, a practically important mixed-element structure is obtained. Then the description of the structure by means of two frequency variables (one for shunt capacitors and one for transmission lines) is detailed: Explicit expressions for the coefficients of the descriptive two-variable polynomials in terms of the coefficients of the single variable boundary polynomials are derived for various numbers of elements, which are obtained first time in the literature. Finally, a mixed-element broadband matching network is designed to illustrate the usage of the obtained expressions. If it is preferred not to have shunt capacitors, they can be replaced with open-ended stubs via Richard's transformation. So the resultant circuit is extremely suitable for microstrip fabrication.
Citation Count: 11
Bound-free electron-positron pair production in relativistic heavy-ion collisions
(Amer Physical Soc., 2009) Şengül, Metin Y.; Güçlü, Mehmet C.; Fritzsche, S.
The bound-free electron-positron pair production is considered for relativistic heavy ion collisions. In particular cross sections are calculated for the pair production with the simultaneous capture of the electron into the 1s ground state of one of the ions and for energies that are relevant for the relativistic heavy ion collider and the large hadron colliders. In the framework of perturbation theory we applied Monte Carlo integration techniques to compute the lowest-order Feynman diagrams amplitudes by using Darwin wave functions for the bound states of the electrons and Sommerfeld-Maue wave functions for the continuum states of the positrons. Calculations were performed especially for the collision of Au+Au at 100 GeV/nucleon and Pb+Pb at 3400 GeV/nucleon.
Citation Count: 22
Broadband Decoupling and Matching of a Superdirective Two-Port Antenna Array
(IEEE-INST Electrical Electronics Engineers Inc, 2008) Volmer, Christian; Şengül, Metin Y.; Weber, Joern; Stephan, Ralf; Hein, Matthias A.
Decoupling and matching networks may be used to improve the performance of compact antenna arrays where mutual radiator coupling has caused a degradation of the diversity capabilities. A popular network consists of a 180 degrees rat-race directional coupler which decouples the antenna ports followed by impedance matching networks at each port. Researchers however usually neglect the presence of losses both within the antenna array and the decoupling and matching network. For this reason we have built various narrowband and broadband matching networks and compare their performances with the help of calibrated far-field measurement data.
Citation Count: 9
Construction of Lossless Ladder Networks With Simple Lumped Elements Connected Via Commensurate Transmission Lines
(IEEE-INST Electrical Electronics Engineers Inc, 2009) Şengül, Metin Y.
In this work an algorithm to design lossless ladder networks with simple lumped elements connected via commensurate transmission lines is proposed. After giving the algorithm a lumped-element low-pass Chebyshev filter was transformed to its mixed-element counterpart to illustrate the utilization of the algorithm. The filter designed for a frequency band around 1 GHz was fabricated and experimentally characterized. We find very good agreement between measured and simulated transducer power gain over the entire frequency band of interest.
Citation Count: 17
Design of Practical Broadband Matching Networks With Lumped Elements
(IEEE-INST Electrical Electronics Engineers Inc, 2013) Şengül, Metin Y.
It is always preferable to use commercially available software tools to design broadband matching networks for microwave communication systems. However for these tools the matching network topology and element values must be selected properly. Therefore in this paper a practical method is presented to generate matching networks with good initial element values. Eventually the performance of the designed matching network is optimized by employing the commercially available computer-aided design (CAD) tools. An example is given to illustrate the utilization of the proposed method. It is shown that the proposed method provides very good initials for CAD tools.
Citation Count: 9
Design of Practical Broadband Matching Networks With Mixed Lumped and Distributed Elements
(IEEE-INST Electrical Electronics Engineers Inc, 2014) Şengül, Metin Y.
Computer-aided design (CAD) tools are always preferred for designing broadband matching networks. However these tools give excellent results when the suitable matching network topology and initial element values are provided. Therefore in this brief a new initialization algorithm is proposed to get suitable network topology and element values for CAD tools. Then the power transfer capability of the matching network can be improved by using any CAD tool. It is clear from the example studied that the new method generates excellent initials.
Citation Count: 25
Design of practical matching networks with lumped elements via modeling
(IEEE, 2007) Yarman, Sıddık Binboğa; Şengül, Metin Y.; Kılınç, Ali
It is a common practice to utilize commercially available software tools to design matching networks for wireless communication systems. Most of these tools require a properly selected matching network topology with good initial element values. Therefore in this paper a practical method is presented to generate matching networks with initial element values. In the implementation process of the proposed method first the driving point immitance data for the matching network is obtained in a straight forward manner without optimization. Then it is modeled as a realizable bounded-real input reflection coefficient which in turn yields the desired matching network with reasonable element values. Eventually the initial design is improved by optimizing the performance of the matched system employing the commercially available computer-aided design (CAD) packages. An example is given to illustrate the utilization of the proposed method. It is shown that new method provides excellent results as a front-end when utilized together with CAD tools.
Citation Count: 7
Energy efficient robust scheduling of periodic sensor packets for discrete rate based wireless networked control systems
(Elsevier, 2020) Şadi, Yalçın; Uçar, Seyhan; Şadi, Yalçın; Coleri, Sinem
Wireless networked control systems (WNCSs) require the design of a robust scheduling algorithm that meets the stringent timing and reliability requirements of control systems, despite the limited battery resources of sensor nodes and adverse properties of wireless communication for delay and packet errors. In this article, we propose a robust delay and energy constrained scheduling algorithm based on the exploitation of the mostly pre-known periodic data generation nature of sensor nodes in control systems. We first formulate the joint optimization of scheduling, power control and rate adaptation for discrete rate transmission model, in which only a finite set of transmission rates are supported, as a Mixed-Integer Non-linear Programming problem and prove its NP-hardness. Next, we propose an optimal polynomial-time power control and rate adaptation algorithm for minimizing the transmission time of a node subset. We then design a novel polynomial-time heuristic scheduling algorithm based on first determining the concurrently transmitting node subsets and then distributing them uniformly over time by a modified Karmarkar-Karp algorithm. We demonstrate the superior performance of the proposed scheduling algorithm in terms of robustness, delay and runtime on the Low-Rate Wireless Personal Area Network (LR-WPAN) simulation platform, which we developed in network simulator-3 (ns3).
Citation Count: 11
Energy Efficient SCMA Supported Downlink Cloud-RANs for 5G Networks
(IEEE, 2020) Erküçük, Serhat; Erküçük, Serhat; Anpalagan, Alagan; Woungang, Isaac
Cloud-radio access networks (C-RANs) are regarded as a promising solution to provide low cost services among users through the centralized coordination of baseband units for 5G wireless networks. The coordinated multi-point access, visualization and cloud computing technologies enable C-RANs to provide higher capacity and wider coverage, as well as manage the interference and mobility in a centralized coordinated way. However, C-RANs face many challenges due to massive connectivity and spectrum scarcity. If not properly handled, these challenges may degrade the overall performance. Recently, the non-orthogonal multiple access (NOMA) scheme has been suggested as an attractive solution to support multi-user resource sharing in order to improve the spectrum and energy efficiency in 5G wireless networks. In this paper, among various NOMA schemes, we consider and implement the sparse code multiple access (SCMA) scheme to jointly optimize the codebook (CB) and power allocation in the downlink of C-RANs, where the utilization of SCMA in C-RANs to improve the energy efficiency has not been investigated in detail in the literature. To solve this NP-hard joint optimization problem, we decompose the original problem into two sub-problems: codebook allocation and power allocation. Using the conflict graph, we propose the throughput aware SCMA CB selection (TASCBS) method, which generates a stable codebook allocation solution within a finite number of steps. For the power allocation solution, we propose the iterative level-based power allocation (ILPA) method, which incorporates different power allocation approaches (e.g., weighted and NOMA successive interference cancellation (SIC)) into different levels to satisfy the maximum power requirement. Simulation results show that the sum data rate and energy efficiency performances of SCMA supported C-RANs depend on the selected power allocation approach. In terms of energy efficiency, the performance significantly improves with the number of users when the NOMA-SIC aware geometric water-filling based power allocation method is used.
Citation Count: 10
Fault-tolerant training of neural networks in the presence of MOS transistor mismatches
(IEEE-INST Electrical Electronics Engineers Inc, 2001) Öğrenci, Arif Selçuk; Dündar, Günhan; Balkır, Sina
Analog techniques are desirable for hardware implementation of neural networks due to their numerous advantages such as small size low power and high speed. However these advantages are often offset by the difficulty in the training of analog neural network circuitry. In particular training of the circuitry by software based on hardware models is impaired by statistical variations in the integrated circuit production process resulting in performance degradation. In this paper a new paradigm of noise injection during training for the reduction of this degradation is presented. The variations at the outputs of analog neural network circuitry are modeled based on the transistor-level mismatches occurring between identically designed transistors Those variations are used as additive noise during training to increase the fault tolerance of the trained neural network. The results of this paradigm are confirmed via numerical experiments and physical measurements and are shown to be superior to the case of adding random noise during training.
Citation Count: 8
An Improved Adaptive Subspace Tracking Algorithm Based on Approximated Power Iteration
(IEEE-INST Electrical Electronics Engineers Inc, 2018) Panayırcı, Erdal; Zheng, Jian-Sheng; Dong, Zhicheng; Panayırcı, Erdal; Wu, Zhi-Qiang; Ren, Qingnuobu
A subspace tracking technique has drawn a lot of attentions due to its wide applications. The main objective of this approach is to estimate signal or noise subspace basis for the sample covariance matrix. In this paper we focus on providing a fast stable and adaptive subspace tracking algorithm that is implemented with low computational complexity. An alternative realization of the fast approximate power iteration (FAPI) method termed modified FAPI (MFAPI) is also presented. Rather than solving an inverse square root of a matrix employed in the FAPI the MFAPI applies the matrix product directly to ensure the orthonormality of the subspace basis matrix at each recursion. This approach yields a simpler derivation and is numerically stable while maintaining a similar computational complexity as compared with that of the FAPI. Furthermore we present a detailed mathematical proof of the numerical stability of our proposed algorithm. Computer simulation results indicate that the MFAPI outperforms many classical subspace tracking algorithms particularly at the transient-state step.
Citation Count: 81
A Mobile Channel Model for VLC and Application to Adaptive System Design
(IEEE-INST Electrical Electronics Engineers Inc, 2017) Miramirkhani, Farshad; Narmanlıoğlu, Ömer; Uysal, Murat; Panayırcı, Erdal
In this letter we propose a realistic channel model for visible light communication (VLC) assuming a mobile user. Based on non-sequential ray tracing we first obtain channel impulse responses for each point over the user movement trajectories and then express path loss and delay spread as a function of distance through curve fitting. Our results demonstrate large variations in received power. In system design this necessitates the use of adaptive schemes where transmission parameters can be selected according to channel conditions. To demonstrate the benefits of link adaptation over a mobile VLC channel we propose an adaptive system with luminary selection and demonstrate improvements in spectral efficiency over non-adaptive systems.
Citation Count: 10
On channel estimation for spatial modulated systems over time-varying channels
(Academic Press Inc Elsevier Science, 2015) Acar, Yusuf; Doğan, Hakan; Panayırcı, Erdal
Spatial Modulation (SM) has been proposed recently for multiple-input multiple-output (MIMO) systems to cope with the interchannel interference and to reduce the detection complexity as compared to the conventional MIMO systems. In SM system the data symbols are transmitted by a randomly selected active antenna of a MIMO transmitter to the receiver through a wireless channel. The information is carried both by the data symbol from any signal constellation such as M-ary phase shift keying (M-PSK) or M-ary quadrature amplitude modulation (M-QAM) by the index of the selected antenna. The channel estimation is a critical process at the receiver during the coherent detection of the transmitted symbol and the antenna index randomly selected. Recently the channel estimation of channel for SM systems has been investigated by the recursive least square (RLS) algorithm for only quasi-static fading channels. In this paper a novel channel estimation is proposed for SM systems in the presence of rapidly time-varying channels. The Bayesian mean square error (MSE) bound has been derived as a benchmark and the performance of the proposed approaches is studied in terms of MSE and bit-error rate (BER). Computer simulation results have confirmed that the proposed iterative channel estimation technique has significant BER/MSE performance advantages compared with existing channel estimation algorithm proposed earlier in the literature. (C) 2014 Elsevier Inc. All rights reserved.
Citation Count: 135
Performance of spatial modulation in the presence of channel estimation errors
(IEEE-INST Electrical Electronics Engineers Inc, 2012) Basar, Ertuğrul; Aygölü, Ümit; Panayırcı, Erdal; Poor, H. Vincent
This work investigates the negative effects of channel estimation errors on the performance of spatial modulation (SM) when operating over flat Rayleigh fading channels. The pairwise error probability of the SM scheme is derived in the presence of channel estimation errors and an upper bound on the average bit error probability is evaluated for M-PSK and M-QAM signalling. It is shown via computer simulations that the derived upper bound becomes very tight with increasing signal-to-noise ratio (SNR) and the SM scheme is quite robust to channel estimation errors.
Citation Count: 30
Performance of transmit and receive antenna selection in the presence of channel estimation errors
(IEEE-INST Electrical Electronics Engineers Inc, 2008) Güçlüoğlu, Tansal; Panayırcı, Erdal
This letter considers the effect of channel estimation errors on the performance of space-time coded (STC) systems with transmit and receive antenna selection over quasi-static flat fading channels. By performing pairwise error probability analysis and presenting numerical examples we show that the diversity order achieved with perfect channel state information (CSI) is still achievable with imperfect CSI used both at the antenna selection and the space-time decoding processes. We note that our results apply to general STC systems with both transmit and/or receive antenna selection based on largest received powers which can be estimated by any channel estimator.
Citation Count: 4
Power and Rate Adaptation Based on CSI and Velocity Variation for OFDM Systems Under Doubly Selective Fading Channels
(IEEE-INST Electrical Electronics Engineers Inc, 2016) Dong, Zhicheng; Fan, Pingzhi; Lei, Xianfu; Panayırcı, Erdal
In this paper a novel joint continuous power and rate adaptation scheme is proposed fordoubly selective fading channels in orthogonal frequency division multiplexing (OFDM) systems based on terminal velocity and perfect or imperfect channel state information (CSI). The analysis and simulation results show that the continuous power and rate adaptation scheme is very effective and improve the performance of OFDM systems substantially under time-varying fading channels as compared with the traditional adaptation schemes operating without a priori knowledge of velocity and mobility adaptation without CSI.
Citation Count: 15
Synthesis of cascaded lossless commensurate lines
(IEEE-INST Electrical Electronics Engineers Inc, 2008) Şengül, Metin Y.
A scattering transfer matrix factorization based algorithm for cascaded lossless commensurate line synthesis is presented. The characteristic impedances of the extracted commensurate lines and the reflection factors of the remaining networks are formulated in terms of reflection factor coefficients of the whole circuit. There is no need to use root search routines so as to cancel common terms to get degree reduction. The formulation. of the method is explained. and an example is included to illustrate the implementation of the synthesis algorithm.
Citation Count: 2
Transmitter source location estimation using crowd data
(Pergamon-Elsevier Science Ltd, 2018) Arsan, Taner; Arsan, Taner
The 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.
Citation Count: 18
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data have a spatial dimension as an additional context which is often expressed in terms of coordinates of the region of interest (such as latitude - longitude information). However, existing techniques are limited to handle spatial and temporal contextual attributes in an integrated and meaningful way considering both spatial and temporal dependency between observations. In this paper, a hybrid deep learning framework is proposed to solve the unsupervised anomaly detection problem in multivariate spatio-temporal data. The proposed framework works with unlabeled data and no prior knowledge about anomalies are assumed. As a case study, we use the public COVID-19 data provided by the Italian Department of Civil Protection. Northern Italy regions' COVID-19 data are used to train the framework; and then any abnormal trends or upswings in COVID-19 data of central and southern Italian regions are detected. The proposed framework detects early signals of the COVID-19 outbreak in test regions based on the reconstruction error. For performance comparison, we perform a detailed evaluation of 15 algorithms on the COVID-19 Italy dataset including the state-of-the-art deep learning architectures. Experimental results show that our framework shows significant improvement on unsupervised anomaly detection performance even in data scarce and high contamination ratio scenarios (where the ratio of anomalies in the data set is more than 5%). It achieves the earliest detection of COVID-19 outbreak and shows better performance on tracking the peaks of the COVID-19 pandemic in test regions. As the timeliness of detection is quite important in the fight against any outbreak, our framework provides useful insight to suppress the resurgence of local novel coronavirus outbreaks as early as possible.

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