Özen, Serdar
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S. Özen
S. Ozen
Özen, Serdar.
Ozen, Serdar.
Özen, S.
Ozen, S.
S. Ozen
Özen, Serdar.
Ozen, Serdar.
Özen, S.
Ozen, S.
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Email Address
serdarozen@iyte.edu.tr
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03.05. Department of Electrical and Electronics Engineering
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Current Staff
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Documents
29
Citations
104
h-index
6
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Scholarly Output
18
Articles
4
Views / Downloads
29085/7600
Supervised MSc Theses
3
Supervised PhD Theses
0
WoS Citation Count
11
Scopus Citation Count
27
Patents
0
Projects
1
WoS Citations per Publication
0.61
Scopus Citations per Publication
1.50
Open Access Source
17
Supervised Theses
3
| Journal | Count |
|---|---|
| 13th European Signal Processing Conference, EUSIPCO 2005 | 1 |
| 2004 IEEE Military Communications Conference | 1 |
| 2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 | 1 |
| 2010 IEEE 11th Annual Wireless and Microwave Technology Conference, WAMICON 2010 -- 2010 IEEE 11th Annual Wireless and Microwave Technology Conference, WAMICON 2010 -- 12 April 2010 through 13 April 2010 -- Melbourne, FL -- 80494 | 1 |
| 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 | 1 |
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18 results
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Now showing 1 - 10 of 18
Conference Object Approximate Best Linear Unbiased Channel Estimation for Frequency Selective Channels With Long Delay Spreads: Robustness To Timing and Carrier Offsets(Institute of Electrical and Electronics Engineers Inc., 2005) Özen, Serdar; Nerayanuru, Sreenivasa M.; Pladdy, Christopher; Fimoff, Mark J.We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols. The iterative procedure calculates the (semi-blind) Best Linear Unbiased Estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, denoted by a-BLUE, achieving almost similar performance, with much lower complexity. Indeed we show that, with reasonable assumptions, a-BLUE channel estimate can be obtained by using a stored copy of a pre-computed matrix in the receiver which enables the use of the initial CIR estimate by the subsequent equalizer tap weight calculator. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC Digital TV system. We also provide a simulation study of the robustness of the a-BLUE algorithm to timing and carrier phase offsets.Master Thesis Constant False Alarm Rate (cfar) Detection Based Estimators With Applications To Sparse Wireless Channels(Izmir Institute of Technology, 2006) Karaca, Ümit; Özen, SerdarWe provide Constant False Alarm Rate (CFAR) based thresholding methods for training based channel impulse response (CIR) estimation algorithms for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols. After obtaining the CIR estimation by using known methods in the literature, there are estimation errors which causes performance loss at equalizers. The channel estimation error can be seen as .noise. on CIR estimations and CFAR based thresholding methods, which are used in radar systems to decide the presence of a target, can effectively overcome this problem. CFAR based methods are based on determining threshold values which are computed by distribution of channel noise. We provide exact and approximate distribution of channel noise appear at CIR estimate schemes. We applied Cell Averaging-CFAR (CA-CFAR) and Order Statistic-CFAR (OSCFAR) methods on the CIR estimations. The performance of the CFAR estimators are then compared by their Least Square error in the channel estimates. The Signal to Interference plus Noise Ratio (SINR) performance of the decision feedback equalizers (DFE), of which the tap values are calculated based on the CFAR estimators, are also provided.Article Citation - WoS: 3Citation - Scopus: 3Hardware Realization of a Low-Complexity Fading Filter for Multipath Rayleigh Fading Simulator(Springer Verlag, 2011) Özen, Serdar; Arsal, Ali; Toker, Kadir AtillaA low-complexity high performance Rayleigh fading simulator, and its Field Programmable Gate Array (FPGA) implementation are presented. This proposed method is a variant of the method of filtering of the white Gaussian noise where the filter design is accomplished in the analog domain and transferred into digital domain. The proposed model is compared with improved Jakes' model, auto-regressive (AR) filtering, existing auto-regressive moving-average (ARMA) filtering techniques, and inverse discrete Fourier transform (IDFT)-based techniques, in performance and computational complexity. The proposed method outperforms AR(20) filter and modified Jakes' generators in performance. Although IDFT method achieves the best performance, it brings a significant cost in storage. The proposed method achieves high performance with the lowest complexity, and its performance has been verified on commercially available FPGA platforms. Our fixed-point Rayleigh fading-channel emulator uses only 2% of the configurable slices, 1% of the Look-Up-Table (LUT) resources and 3% of the dedicated multipliers on the FPGA platform that has been used.Article Citation - WoS: 2Citation - Scopus: 4Constraint Removal for Sparse Signal Recovery(Elsevier Ltd., 2012) Şahin, Ahmet; Özen, SerdarThis paper presents a new iterative algorithm called constraint removal (CR) for the recovery of a sparse signal x from an incomplete number of linear measurements y such that ym× 1= Am× nxn× 1 and m<n. It is empirically demonstrated that the CR algorithm has a recovery performance which is between basis pursuit linear programming (BP-LP) and subspace pursuit (SP) for both zero-one and Gaussian type signals.Article Citation - WoS: 4Citation - Scopus: 6Semiblind Blue Channel Estimation With Applications To Digital Television(Institute of Electrical and Electronics Engineers Inc., 2006) Pladdy, Christopher; Özen, Serdar; Nerayanuru, Sreenivasa M.; Zoltowski, Michael; Fimoff, MarkA semiblind iterative algorithm to construct the best linear unbiased estimate (BLUE) of the channel impulse response (CIR) vector h for communication systems that utilize a periodically transmitted training sequence within a continuous stream of information symbols is devised. The BLUE CIR estimate for the general linear model y = Ah + w, where w is the correlated noise, is given by the Gauss-Markoff theorem. The covariance matrix of the correlated noise, which is denoted by C(h), is a function of the channel that is to be identified. Consequently, an iteration is used to give successive approximations h(k), k = 0, 1, 2,...to hBLUE, where h(0) is an initial approximation given by the correlation processing, which exists at the receiver for the purpose of frame synchronization. A function F(h) for which hBLUE is a fixed point is defined. Conditions under which hBLUE is the unique fixed point and for which the iteration proposed in the algorithm converges to the unique fixed point hBLUE are given. The proofs of these results follow broadly along the lines of Banach fixed-point theorems.Master Thesis Parameter Estimation for Linear Dynamical Systems With Applications To Experimental Modal Analysis(Izmir Institute of Technology, 2008) Tanyer, İlker; Özen, SerdarIn this study the fundamentals of structural dynamics and system identification have been studied. Then some fundamental parameter estimation algorithms in the literature are provided. These algorithms will be applied to an experimental and an artificial system to extract their structural properties. Consequently, the main objective of this study is constructing the mathematical model of a structure by using only the measurement data.To process measurement data, three fundamental modal analysis algorithms are examined. Least-Squares Complex Exponential(LSCE), Eigensystem Realization Algorithm( ERA) and Polyreference Frequency Domain(PFD) algorithms are implemented in MATLAB environment. We applied these algorithms to artificial and experimental data, then we compared the performance of these algorithms. State estimation for linear dynamical systems have also been studied, and details of the Kalman filter as a state estimator are provided. Kalman filter as a state estimator has been integrated with the ERA algorithm and the performance of the Kalman-ERA is provided.Conference Object Consistency Analysis of Kalman Filter for Modal Analysis of Structures(Institute of Electrical and Electronics Engineers Inc., 2009) Tanyer, İlker; Özen, Serdar; Dönmez, Cemalettin; Altınkaya, Mustafa AzizIn this paper, Consistency Analysis of Kalman Filter for Modal Analysis of Structural Systems is made. As a future work, A fundamental Modal Analysis algorithm, Eigensystem Realization Algorithm(ERA) will be used with Kalman filters together to make a modal parameter estimation for a structural system. By applying ERA to the impulse response measurements taken from the structure, a state-space representation will be written. Kalman filter will be used as a state estimator in this study and it will have a critical role on minimizing the measurement noise. Before using Kalman filter with ERA, a consistency analysis of Kalman filter is made for artificial impulse response data of the structural system.Conference Object Citation - Scopus: 3Taylor Series Approximation for Low Complexity Semi-Blind Best Linear Unbiased Channel Estimates for the General Linear Model With Applications To Dtv(IEEE Computer Society, 2004) Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark; Özen, Serdar; Zoltowski, MichaelWe present a low complexity approximate method for semi-blind best linear unbiased estimation (BLUE) of a channel impulse response vector (CIR) for a communication system which utilizes a periodically transmitted training sequence, within a continuous stream of information symbols. The algorithm achieves slightly degraded results at a much lower complexity than directly computing the BLUE CIR estimate. In addition, the inverse matrix required to invert the weighted normal equations to solve the general least squares problem may be precomputed and stored at the receiver. The BLUE estimate is obtained by solving the general linear model, y = Ah + w + n, for h, where w is correlated noise and the vector n is an AWGN process, which is uncorrelated with w. The solution is given by the Gauss-Markoff Theorem as h = (A TC(h) -1A) -1 A TC(h) -1y. In the present work we propose a Taylor series approximation for the function F(h) = (A TC(h) -1A) -1 A TC(h) -1y where, F: R L → R L for each fixed vector of received symbols, y, and each fixed convolution matrix of known transmitted training symbols, A. We describe the full Taylor formula for this function, F (h) = F (h id + ∑ |α|≥1(h - h id) α (∂/∂h) α F(h id) and describe algorithms using, respectively, first, second and third order approximations. The algorithms give better performance than correlation channel estimates and previous approximations used at only a slight increase in complexity. The linearization procedure used is similar to that used in the linearization to obtain the extended Kalman filter, and the higher order approximations are similar to those used in obtaining higher order Kalman filter approximations,Conference Object Citation - Scopus: 5A Fading Filter Design for Multipath Rayleigh Fading Simulation and Comparisons To Other Simulators(Institute of Electrical and Electronics Engineers Inc., 2008) Arsal, Ali; Özen, SerdarA low-complexity high performance Rayleigh fading simulator, an ARMA(3,3) model, is proposed. This proposed method is a variant of the method of filtering of the white Gaussian noise where the filter design is accomplished in the analog domain and transferred into digital domain. The proposed model is compared with improved Jakes' model, autoregressive filtering and IDFT techniques, in performance and computational complexity. Proposed method outperforms AR(20) filter and modified Jakes' generators in performance. Although IDFT method achieves the best performance, it brings a significant cost in storage and is undesirable. The proposed method achieves high performance with the lowest complexity.Conference Object Citation - Scopus: 1Fpga Implementation of a Low-Complexity Fading Filter for Multipath Rayleigh Fading Simulator(Institute of Electrical and Electronics Engineers Inc., 2011) Toker, Kadir Atilla; Özen, Serdar; Arsal, AliA low-complexity high performance Rayleigh fading simulator and its Field Programmable Gate Array (FPGA) implementation are presented. This proposed method is a variant of the method of filtering of the white Gaussian noise where the filter design is accomplished in the analog domain and transferred into digital domain. The proposed method outperforms AR(20) filter and modified Jakes' generators in performance. Although IDFT method achieves the best performance, it brings a significant cost in storage. The proposed method achieves high performance with the lowest complexity, and its performance has been verified on commercially available FPGA platforms. © 2011 IEEE.