Şenol, Habib
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Şenol, Habib
H.,Şenol
H. Şenol
Habib, Şenol
Senol, Habib
H.,Senol
H. Senol
Habib, Senol
Senol, H.
Şenol,H.
Senol, H
Şenol, Habib
H.,Şenol
H. Şenol
Habib, Şenol
Senol, Habib
H.,Senol
H. Senol
Habib, Senol
Senol, H.
Şenol,H.
Senol, H
Şenol, Habib
Job Title
Doç. Dr.
Email Address
Main Affiliation
Computer Engineering
Computer Engineering
05. Faculty of Engineering and Natural Sciences
01. Kadir Has University
Computer Engineering
05. Faculty of Engineering and Natural Sciences
01. Kadir Has University
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
4
QUALITY EDUCATION
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
13
CLIMATE ACTION
0
Research Products
14
LIFE BELOW WATER
0
Research Products
2
ZERO HUNGER
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
1
NO POVERTY
0
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
15
LIFE ON LAND
0
Research Products
3
GOOD HEALTH AND WELL-BEING
1
Research Products
7
AFFORDABLE AND CLEAN ENERGY
2
Research Products
5
GENDER EQUALITY
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output
49
Articles
21
Views / Downloads
23/0
Supervised MSc Theses
3
Supervised PhD Theses
0
WoS Citation Count
345
Scopus Citation Count
454
WoS h-index
9
Scopus h-index
11
Patents
0
Projects
0
WoS Citations per Publication
7.04
Scopus Citations per Publication
9.27
Open Access Source
33
Supervised Theses
3
| Journal | Count |
|---|---|
| IEEE Transactions on Signal Processing | 7 |
| IEEE Transactions on Wireless Communications | 3 |
| Wireless Personal Communications | 2 |
| 2008 IEEE International Conference on Acoustics, Speech and Signal Processing | 1 |
| 2009 IEEE 10th Workshop on Signal Processing Advances in Wireless Communications | 1 |
Current Page: 1 / 6
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49 results
Scholarly Output Search Results
Now showing 1 - 10 of 49
Conference Object Citation - WoS: 3Pilot-Aided Bayesian Mmse Channel Estimation for Ofdm Systems(Ieee, 2004) Senol, H; Çirpan, HA; Panayirci, EThis 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 hound 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.Conference Object Mp-Sage Based Channel Estimation for Underwater Cooperative Ofdm Systems(IEEE, 2013) Erdoğan, Mustafa; Şenol, Habib; Panayırcı, Erdal; Uysal, MuratIn this paper an efficient channel estimation algorithm is proposed for amplify-and-forward (AF) cooperative relay based orthogonal frequency division multiplexing (OFDM) system in the presence of sparse underwater acoustic channels and of the correlative non-Gaussian noise The algorithm is based on the combinations of the matching pursuit (MP) and the space-alternating generalized expectation-maximization (SAGE) technique to improve the estimates of the channel taps and their location as well as the Gaussian mixture noise distribution parameters in an iterative way Computer simulations show that underwater acoustic channel is estimated very effectively and the proposed algorithm has excellent symbol error rate (SER) and channel estimation performance as compared to the existing onesConference Object Effect of Inter-Block Region on Compressed Sensing Based Channel Estimation in Tds-Ofdm Systems(IEEE, 2016) Başaran, Mehmet; Erküçük, Serhat; Şenol, Habib; Cirpan, Hakan AliTime 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 received signal in guard interval can be decomposed into a small-sized signal that contains only PN sequences utilizing the inter-block-interference (IBI)-free region in the convolution matrix. Due to sparsity multipath fading channel can be obtained by the application of compressed sensing (CS) technique to reconstruct the high-dimensional sparse channel from the decreased-size of received signal through the known PN sequence matrix. In this study the effect of the size of IBI-free region on CS and Bayesian CS (BCS) based channel estimation is investigated. Accordingly reconstruction error performances of basis pursuit (BP) and BCS are compared. Simulation results show that the channel estimation can be improved by trading-off the length of the IBI-free region. However an increase in IBI-free region leads to decreased energy efficiency at both the transmitter and receiver side.Article Citation - WoS: 4Citation - Scopus: 6Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems(Springer, 2018) Özmen, Atilla; Şenol, HabibIn 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.Article Citation - WoS: 1Citation - Scopus: 1Bayesian Estimation of Discrete-Time Cellular Neural Network Coefficients(TUBITAK Scientific & Technical Research Council Turkey, 2017) Özer, Hakan Metin; Özmen, Atilla; Şenol, HabibA 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.Article Citation - WoS: 40Citation - Scopus: 51Sparse Channel Estimation and Equalization for Ofdm-Based Underwater Cooperative Systemsw With Amplify-And Relaying(IEEE-INST Electrical Electronics Engineers Inc, 2016) Panayırcı, Erdal; Şenol, Habib; Uysal, Murat; Poor, H. VincentThis paper is concerned with a challenging problem of channel estimation and equalization for amplify-and-forward cooperative relay based orthogonal frequency division multi-plexing (OFDM) systems in sparse underwater acoustic (UWA) channels. The sparseness of the channel impulse response and prior information for the non-Gaussian channel gains modeled by an exact continuous Gaussian mixture (CGM) are exploited to improve the performance of the channel estimation algorithm. The resulting novel algorithm initially estimates the overall sparse complex-valued channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The effective time-domain non-Gaussian noise is approximated well as a Gaussian noise in the frequency-domain where the estimation takes place. An efficient and low complexity algorithm is developed based on a combination of the MP and the maximum a posteriori probability (MAP) based space-alternating generalized expectation-maximization technique to improve the estimates of the channel taps and their locations in an iterative manner. Computer simulations show that the UWA channel is estimated very effectively and the proposed algorithm exhibits excellent symbol error rate and channel estimation performance.Conference Object Citation - Scopus: 4Pilot-Aided Bayesian Mmse Channel Estimation for Ofdm Systems: Algorithm and Performance Analysis(2004) Şenol, Habib; Cirpan, Hakan Ali; Panayırcı, ErdalThis 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.Article Citation - WoS: 7Citation - Scopus: 11Artificial Neural Network Based Estimation of Sparse Multipath Channels in Ofdm Systems(SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2021) Şenol, Habib; Abdur Rehman Bin, Tahir; Özmen, Atilla; Bin Tahir, Abdur RehmanIn order to increase the transceiver performance in frequency selective fading channel environment, orthogonal frequency division multiplexing (OFDM) system is used to combat inter-symbol-interference. In this work, a channel estimation scheme for an OFDM system in the presence of sparse multipath channel is studied using the artificial neural networks (ANN). By means of ANN's learning capability, it is shown that how to model and obtain a channel estimate and how it allows the proposed technique to give a better system throughput. The performance of proposed method is compared with the Matching Pursuit (MP) and Orthogonal MP (OMP) algorithms that are commonly used in compressed sensing literature in order to estimate delay locations and tap coefficients of a sparse multipath channel. In this work, we propose a performance- efficient ANN based sparse channel estimator with lower computational cost than that of MP and OMP based channel estimators. Even though there is a slight performance lost in a few simulation scenarios in which we have lower computational complexity advantage, in most scenarios, our computer simulations corroborate that our low complexity ANN based channel estimator has better mean squared error and the corresponding symbol error rate performances comparing with MP and OMP algorithms.Conference Object Frequency selective fading channel estimation in OFDM systems using KL expansion(2005) Şenol, Habib; Cirpan, Hakan Ali; Panayırcı, ErdalThis 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 studied through analytical and experimental results. We provide performance analysis results studying the influence of the effect of SNR and correlation mismatch on the estimator performance. Simulation results confirm our theoretical results and illustrate that the proposed algorithm is capable of tracking fast fading and improving performance.Article Citation - WoS: 4Citation - Scopus: 6A 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, ErdalFocusing 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.
