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
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ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
15
LIFE ON LAND
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
14
LIFE BELOW WATER
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
3
GOOD HEALTH AND WELL-BEING
1
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
4
QUALITY EDUCATION
0
Research Products
2
ZERO HUNGER
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
2
Research Products
13
CLIMATE ACTION
0
Research Products
1
NO POVERTY
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
5
GENDER EQUALITY
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output
48
Articles
20
Views / Downloads
262/5481
Supervised MSc Theses
3
Supervised PhD Theses
0
WoS Citation Count
345
Scopus Citation Count
451
WoS h-index
9
Scopus h-index
11
Patents
0
Projects
0
WoS Citations per Publication
7.19
Scopus Citations per Publication
9.40
Open Access Source
32
Supervised Theses
3
Google Analytics Visitor Traffic
| 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 |
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48 results
Scholarly Output Search Results
Now showing 1 - 10 of 48
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: 49Sparse 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.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: 7Citation - Scopus: 7Outage Scaling Laws and Diversity for Distributed Estimation Over Parallel Fading Channels(IEEE, 2009) Bai, Kai; Şenol, Habib; Tepedelenlioğlu, CihanWe consider scaling laws of the outage for distributed estimation problems over fading channels with respect to the total power and the number of sensors. Using a definition of diversity which involves a fixed number of sensors we find tight upper and lower bounds on diversity which are shown to depend on the sensing (measurement) signal-to-noise ratios (SNRs) of the sensors. Our results indicate that the diversity order can be smaller than the number of sensors and adding new sensors might not add to the diversity order depending on the sensing SNR of the added sensor. We treat a large class of envelope distributions for the wireless channel including those appropriate for line of sight scenarios. Finally we consider fixed power per sensor with an asymptotically large number of sensors and show that the outage decays faster than exponentially in the number of sensors.Article Citation - WoS: 34Citation - Scopus: 47Performance of Distributed Estimation Over Unknown Parallel Fading Channels(IEEE-INST Electrical Electronics Engineers Inc, 2008) Şenol, Habib; Tepedelenlioglu, CihanWe consider distributed estimation of a source in additive Gaussian noise observed by sensors that are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. We adopt a two-phase approach of i) channel estimation with training and ii) source estimation given the channel estimates and transmitted sensor observations where the total power is fixed. In the second phase we consider both an equal power scheduling among sensors and an optimized choice of powers. We also optimize the percentage of total power that should be allotted for training. We prove that 50% training is optimal for equal power scheduling and at least 50% is needed for optimized power scheduling. For both equal and optimized cases a power penalty of at least 6 dB is incurred compared to the perfect channel case to get the same mean squared error performance for the source estimator. However the diversity order is shown to be unchanged in the presence of channel estimation error. In addition we show that unlike the perfect channel case increasing the number of sensors will lead to an eventual degradation in performance. We approximate the optimum number of sensors as a function of the total power and noise statistics. Simulations corroborate our analytical findings.Conference Object Citation - WoS: 1Citation - Scopus: 4Channel Estimation in Underwater Cooperative Ofdm System With Amplify-And Relaying(IEEE, 2012) Şenol, Habib; Panayırcı, Erdal; Erdoğan, Mustafa; Uysal, MuratThis paper is concerned with a challenging problem of channel estimation for amplify-and-forward cooperative relay based orthogonal frequency division multiplexing (OFDM) systems in the presence of sparse underwater acoustic channels and of the correlative non-Gaussian noise. We exploit the sparse structure of the channel impulse response to improve the performance of the channel estimation algorithm due to the reduced number of taps to be estimated. The resulting novel algorithm initially estimates the overall sparse channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The correlated non-Gaussian effective noise is modeled as a Gaussian mixture. Based on the Gaussian mixture model an efficient and low complexity algorithm is developed based on the combinations of the 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 noise distribution parameters in an iterative way. The proposed SAGE algorithm is designed in such a way that by choosing the admissible hidden data properly on which the SAGE algorithm relies a subset of parameters is updated for analytical tractability and the remaining parameters for faster convergence Computer simulations show that underwater acoustic (UWA) channel is estimated very effectively and the proposed algorithm has excellent symbol error rate and channel estimation performance.Article Citation - WoS: 8Citation - Scopus: 8Optimal Training for Residual Self-Interference for Full-Duplex One-Way Relays(IEEE-INST Electrical Electronics Engineers Inc, 2018) Li, Xiaofeng; Tepedelenlioglu, Cihan; Şenol, HabibChannel estimation and optimal training sequence design for full-duplex one-way relays are investigated. We propose a training scheme to estimate the residual self-interference (RSI) channel and the channels between nodes simultaneously. A maximum likelihood estimator is implemented with the Broyden-Fletcher-Goldfarb-Shanno algorithm. In the presence of RSI the overall source-to-destination channel becomes an inter-symbol-interference (ISI) channel. With the help of estimates of the RSI channel the destination is able to cancel the ISI through equalization. We derive and analyze the Cramer-Rao bound (CRB) in closed-form by using the asymptotic properties of Toeplitz matrices. The optimal training sequence is obtained by minimizing the CRB. Extensions for the fundamental one-way relay model to the frequency-selective fading channels and the multiple relays case are also considered. For the former we propose a training scheme to estimate the overall channel and for the latter the CRB and the optimal number of relays are derived when the distance between the source and the destination is fixed. Simulations using LTE parameters corroborate our theoretical results.
