Browsing by Author "Cirpan, Hakan Ali"
Now showing items 1-20 of 20
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A low-complexity KL expansion-based channel estimator for OFDM systems
This paper first proposes a computationally efficient pilot-aided linear minimum mean square error (MMSE) batch channel estimation algorithm for OFDM systems in unknown wireless fading channels. The proposed approach employs a convenient representation of the discrete multipath fading channel 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 ...
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Bayesian Compressive Sensing For Primary User Detection
Authors:Başaran, Mehmet; Erküçük, Serhat; Cirpan, Hakan Ali
Publisher and Date:(Inst Engineering Technology-IET, 2016)In compressive sensing (CS)-based spectrum sensing literature most studies consider accurate reconstruction of the primary user signal rather than detection of the signal. Furthermore possible absence of the signal is not taken into account while evaluating the spectrum sensing performance. In this study Bayesian CS is studied in detail for primary user detection. In addition to assessing the signal reconstruction performance and comparing it with the conventional basis pursuit approach and the ...
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Bayesian compressive sensing for ultra-wideband channel models
Considering the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically we investigate the effects of (i) ...
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Compressive sensing for ultra-wideband channel estimation: on the sparsity assumption of ultra-wideband channels
Authors:Başaran, Mehmet; Erküçük, Serhat; Cirpan, Hakan Ali
Publisher and Date:(Wiley-Blackwell, 2014)Due to the sparse structure of ultra-wideband (UWB) multipath channels there has been a considerable amount of interest in applying the compressive sensing (CS) theory to UWB channel estimation. The main consideration of the related studies is to propose different implementations of the CS theory for the estimation of UWB channels which are assumed to be sparse. In this study we investigate the suitability of standardized UWB channel models to be used with the CS theory. In other words we question ...
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Data-Aided Autoregressive Sparse Channel Tracking for OFDM Systems
Authors:Buyuksar, Ayse Betul; Şenol, Habib; Erküçük, Serhat; Cirpan, Hakan Ali
Publisher and Date:(IEEE, 2016)In order to meet future communication system requirements channel estimation over fast fading and frequency selective channels is crucial. In this paper Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also an initialization algorithm has been developed from the widely used sparse approximation ...
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Effect of Inter-Block-Interference-Free Region on Compressed Sensing Based Channel Estimation in TDS-OFDM Systems
Authors:Başaran, Mehmet; Erküçük, Serhat; Şenol, Habib; Cirpan, Hakan Ali
Publisher and Date:(IEEE, 2016)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 ...
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EM-MAP based initialization of PIC receiver for downlink MC-CDMA systems
The quality of multiple access interference (MAI) which can be improved by using channel estimation and data estimation of all active users effects considerably the performance of PIC detector. Therefore data and channel estimation performance is obtained in the initial stage has a significant relationship with the performance of PIC. So obviously it is necessary to make excellent joint data and channel estimation for initialization of PIC detector. In this work to initiate PIC module efficiently ...
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Frequency selective fading channel estimation in OFDM systems using KL expansion
This paper proposes a computationally efficient linear minimum mean square error (MMSE) channel estimation algorithm based on KL series expansion for OFDM systems. Based on such expansion no matrix inversion is required in the proposed MMSE estimator. Moreover truncation in the linear expansion of channel is achieved 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 ...
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Iterative channel estimation techniques for uplink MC-CDMA systems
In this work maximum likelihood (ML) channel estimation for uplink multicarrier code-division multiple-access (MC-CDMA) systems is considered in the presence of frequency fading channel. The expectation-maximization (EM)- and a space-alternating generalized expectation-maximization (SAGE) algorithm are introduced to avoid matrix inversion for the ML channel estimation problem. We compare the both algorithms in terms of the number of used iteration and show that the proposed algorithms converge the ...
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Iterative joint data detection and channel estimation for uplink MC-CDMA systems in the presence of frequency selective channels
Authors:Panayirci, Erdal; Dogan, Hakan; Cirpan, Hakan Ali; Kocian, Alexander; Fleury, Bernard Henri
Publisher and Date:(2010)This paper is concerned with joint multiuser detection and multichannel estimation (JDE) for uplink multicarrier code-division multiple-access (MC-CDMA) systems in the presence of frequency selective channels. The detection and estimation implemented at the receiver are based on a version of the expectation maximization (EM) algorithm and the space-alternating generalized expectation-maximization (SAGE) which are very suitable for multicarrier signal formats. The EM-JDE receiver updates the data ...
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Iterative receiver for DS-CDMA systems in the presence of time-varying channels
In this paper we present an efficient iterative receiver structure of tractable complexity for joint multiuser detection and multichannel estimation (JDE) ofdirect-sequence code-division multiple-access systems operating in the presence of timevarying flat fading channel. The tilne-varying channel is assumed to be modeled according to a piece-wise constant channel. An optimality criterion is defined and analytical expressions for the corresponding optimized weight coefficients are given. Monte-Carlo ...
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Monte Carlo Solutions for Blind Phase Noise Estimation
Authors:Simoens, Frederik; Duyck, Dieter; Cirpan, Hakan Ali; Panayirci, Erdal; Moeneclaey, Marc
Publisher and Date:(Springer International Publishing Ag, 2009)This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN) channels. The main contributions of the paper are (i) the development of a Monte Carlo framework for phase noise estimation with special attention to sequential importance sampling and Rao-Blackwellization (ii) the interpretation of existing Monte Carlo solutions within this generic framework and (iii) the derivation of a novel phase noise estimator. Contrary to the ...
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Near field parameter estimation of moving sources with recursive expectation maximization algorithm
Authors:Cekli, Serap; Cekli, Erdinc; Kabaoǧlu, Nihat; Cirpan, Hakan Ali
Publisher and Date:(IEEE, 2006)In this paper maximum likelihood (ML) estimator is proposed for the joint estimation of the direction of arrival (DOA) and range parameters of moving sources in the near-field of the antenna array. ML estimation algorithm is presented for deterministic signal model. Recursive form of the expectation maximization (REM) algoritm is suggested for the estimation of the near-field parameters because there is not closed form solutions for the maximum likelihood functions. Moreover simulation results of ...
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Near field parameter estimation of moving sources with recursive expectation maximization algorithm [Yinelemeli beklenti/en büyükleme algoritması ile hareketli kaynakların yakın-alan parametrelerinin kestirimi]
In this paper maximum likelihood (ML) estimator is proposed for the joint estimation of the direction of arrival (DOA) and range parameters of moving sources in the near-field of the antenna array. ML estimation algorithm is presented for deterministic signal model. Recursive form of the expectation maximization (REM) algoritm is suggested for the estimation of the near-field parameters because there is not closed form solutions for the maximum likelihood functions. Moreover simulation results of ...
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Pilot-aided bayesian MMSE channel estimation for OFDM systems: Algorithm and performance analysis
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 ...
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Rapidly Varying Sparse Channel Tracking with Hybrid Kalman-OMP Algorithm
Authors:Büyükşar, Ayşe Betül; Şenol, Habib; Erküçük, Serhat; Cirpan, Hakan Ali
Publisher and Date:(Springer, 2019)It is expected from future communication standards that channel estimation algorithms should be able to operate over very fast varying frequency selective channel models. Therefore in this study autoregressive (AR) modeled fast varying channel has been considered and tracked with Kalman filter over one orthogonal frequency division multiplexing (OFDM) symbol. Channel sparsity is exploited which decreases the complexity requirements of the Kalman algorithm. Since Kalman filter is not directly ...
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Support vector machines based target tracking techniques [Destek vektör makineleri tabanlı hedef takip yöntemleri]
This paper addresses the problem of aplying powerful statistical pattern classification algorithms based on kernels to target tracking. Rather than directly adapting a recognizer we develop a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers using dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the tracker is demostrated in a sensor ...
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Support vector regression for surveillance purposes
This paper addresses the problem of applying powerful statistical pattern classification algorithm based on kernel functions to target tracking on surveillance systems. Rather than directly adapting a recognizer we develop a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers to use dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the ...
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The effect of channel resolution on compressed sensing based Ultra-Wideband channel estimation [Kanal çözünürlüǧünün sıkıştırılmış algılama tabanlı ultra geni̇ş bantlı kanal kesti̇ri̇mi̇ne etki̇si̇]
Ultra short pulses are transmitted in Ultra-Wideband (UWB) communications. As a result of this pulses at the receiver can be resolved individually due to the sparse structure of the channel. Due to these properties the UWB channel can be estimated by using a compressed sensing based channel estimation method. The performance of channel estimation depends on the sparsity of the channel. In this work the effect of channel resolution which directly affects the sparsity is examined. It is shown that ...
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The Effect of Primary User Bandwidth on Bayesian Compressive Sensing Based Spectrum Sensing
Authors:Başaran, Mehmet; Erküçük, Serhat; Cirpan, Hakan Ali
Publisher and Date:(IEEE Computer Society, 2016)The application of compressive sensing (CS) theory has found great interest in wideband spectrum sensing. Although most studies have considered perfect reconstruction of the primary user signal it is actually more important to assess the presence or absence of the signal. Among CS based methods Bayesian CS (BCS) takes into consideration the prior information of signal coefficients to be estimated which improves signal reconstruction performance. On the other hand the sparsity level of the signal ...