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
Job Title
Doç. Dr.
Email Address
Main Affiliation
Computer Engineering
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
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WoS Researcher ID

Sustainable Development Goals

11

SUSTAINABLE CITIES AND COMMUNITIES
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17

PARTNERSHIPS FOR THE GOALS
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14

LIFE BELOW WATER
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8

DECENT WORK AND ECONOMIC GROWTH
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15

LIFE ON LAND
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1

NO POVERTY
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7

AFFORDABLE AND CLEAN ENERGY
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2

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6

CLEAN WATER AND SANITATION
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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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3

GOOD HEALTH AND WELL-BEING
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2

ZERO HUNGER
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4

QUALITY EDUCATION
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10

REDUCED INEQUALITIES
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13

CLIMATE ACTION
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GENDER EQUALITY
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This researcher does not have a Scopus ID.
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Scholarly Output

49

Articles

21

Views / Downloads

280/6034

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

JournalCount
IEEE Transactions on Signal Processing7
IEEE Transactions on Wireless Communications3
Wireless Personal Communications2
2008 IEEE International Conference on Acoustics, Speech and Signal Processing1
2009 IEEE 10th Workshop on Signal Processing Advances in Wireless Communications1
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Scholarly Output Search Results

Now showing 1 - 10 of 49
  • Article
    Citation - WoS: 15
    Citation - Scopus: 16
    Rapidly Time-Varying Channel Estimation for Full-Duplex Amplify-And One-Way Relay Networks
    (IEEE-INST Electrical Electronics Engineers Inc, 2018) Şenol, Habib; Li, Xiaofeng; Tepedelenlioglu, Cihan
    Estimation of both cascaded and residual self-interference (RSI) channels and a new training frame structure are considered for full-duplex (FD) amplify-and-forward (AF) one-way relay networks with rapidly time-varying individual channels. To estimate the RSI and the rapidly time-varying cascaded channels we propose a new training frame structure in which orthogonal training blocks are sent by the source node and delivered to the destination over an FD-AF relay. Exploiting the orthogonality of the training blocks we obtain two decoupled training signal models for the estimation of the RSI and the cascaded channels. We apply linear minimum mean square error (MMSE) based estimators to the cascaded channel as well as RSI channel. In order to investigate the mean square error (MSE) performance of the system we also derive the Bayesian Cramer-Rao lower bound. As another performance benchmark we also assess the symbol error rate (SER) performances corresponding to the estimated and the perfect channel state information available at the receiver side. Computer simulations exhibit the proposed training frame structure and the linear MMSE estimator MSE and SER performances are shown.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 11
    Artificial 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 Rehman
    In 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
    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 Ali
    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 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: 7
    Citation - Scopus: 7
    Outage Scaling Laws and Diversity for Distributed Estimation Over Parallel Fading Channels
    (IEEE, 2009) Bai, Kai; Şenol, Habib; Tepedelenlioğlu, Cihan
    We 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.
  • Conference Object
    Citation - WoS: 4
    Performance Investigation of Ieee 802.11af Systems Under Realistic Channel Conditions
    (IEEE, 2015) Macit, Mustafa Can; Şenol, Habib; Erküçük, Serhat
    As the analog TV broadcasting channels have become less frequently used in the last decade there has been a great interest in these frequency bands for the deployment of metropolitan local and personal area networks. Among them the local area network standard IEEE 802.11af defines PHY and MAC layer implementation of such networks in these unused frequency bands also named television white space (TVWS). According to the standard the systems may use contiguous or non-contiguous channels during their operation depending on the channel availability. In this paper we investigate in detail the performance of different operation modes of these systems under realistic channel conditions. While the perfect knowledge of channel would result in similar system performances as the number of in-between-bands occupying the non-contiguous modes is increased the channel estimation performance degrades drastically which is quantified in this study. In addition it is shown that determining the true locations of multipaths heavily relies on the selected channel resolution and has a significant effect on the system performance. Numerical examples are given to demonstrate the effects of both the non-contiguous operation modes and the selected channel resolution.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 6
    Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems
    (Springer, 2018) Özmen, Atilla; Şenol, Habib
    In 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: 1
    Citation - Scopus: 1
    Bayesian Estimation of Discrete-Time Cellular Neural Network Coefficients
    (TUBITAK Scientific & Technical Research Council Turkey, 2017) Özer, Hakan Metin; Özmen, Atilla; Şenol, Habib
    A 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: 40
    Citation - Scopus: 51
    Sparse 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. Vincent
    This 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: 4
    Pilot-Aided Bayesian Mmse Channel Estimation for Ofdm Systems: Algorithm and Performance Analysis
    (2004) Şenol, Habib; Cirpan, Hakan Ali; Panayırcı, Erdal
    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 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: 4
    Citation - Scopus: 6
    A 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, Erdal
    Focusing 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.