Şenol, Habib

Şenol, Habib

Name Variants

Şenol, Habib
H.,Şenol
H. Şenol
Habib, Şenol
Senol, Habib
H.,Senol
H. Senol
Habib, Senol
Senol, H.
Şenol,H.
Senol, H

Job Title

Doç. Dr.

Email Address

Hsenol@khas.edu.tr

Main Affiliation

Computer Engineering

Status

Former Staff

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Scholarly Output

47

Articles

20

Citation Count

0

Supervised Theses

1 Scholarly Output Search Results

Now showing 1 - 10 of 20

Citation - WoS: 4
Citation - Scopus: 6
Channel Estimation for Realistic Indoor Optical Wireless Communication in Aco-Ofdm Systems
(Springer, 2018) Özmen, Atilla; Özmen, Atilla; Şenol, Habib; Şenol, Habib; Computer Engineering; Electrical-Electronics Engineering
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.
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; Şenol, Habib; Özmen, Atilla; Özmen, Atilla; Şenol, Habib; Computer Engineering; Electrical-Electronics Engineering
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.
Citation - WoS: 38
Citation - Scopus: 48
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; Şenol, Habib; Panayırcı, Erdal; Uysal, Murat; Poor, H. Vincent; Computer Engineering; Electrical-Electronics Engineering
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.
Citation - WoS: 33
Citation - Scopus: 46
Performance of Distributed Estimation Over Unknown Parallel Fading Channels
(IEEE-INST Electrical Electronics Engineers Inc, 2008) Şenol, Habib; Şenol, Habib; Tepedelenlioglu, Cihan; Computer Engineering
We 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.
Citation - WoS: 14
Citation - Scopus: 14
Rapidly Time-Varying Channel Estimation for Full-Duplex Amplify-And One-Way Relay Networks
(IEEE-INST Electrical Electronics Engineers Inc, 2018) Şenol, Habib; Şenol, Habib; Li, Xiaofeng; Tepedelenlioglu, Cihan; Computer Engineering
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.
Citation - WoS: 7
Citation - Scopus: 7
Outage Scaling Laws and Diversity for Distributed Estimation Over Parallel Fading Channels
(IEEE, 2009) Bai, Kai; Şenol, Habib; Şenol, Habib; Tepedelenlioğlu, Cihan; Computer Engineering
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.
Citation - WoS: 36
Citation - Scopus: 36
Nondata-Aided Joint Channel Estimation and Equalization for Ofdm Systems in Very Rapidly Varying Mobile Channels
(IEEE-INST Electrical Electronics Engineers Inc, 2012) Şenol, Habib; Şenol, Habib; Panayırcı, Erdal; Panayırcı, Erdal; Poor, H. Vincent; Computer Engineering; Electrical-Electronics Engineering
This paper is concerned with the challenging and timely problem of joint channel estimation and equalization for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The resulting algorithm is based on the space alternating generalized expectation maximization-maximum a posteriori probability (SAGE-MAP) technique which is particularly well suited to multicarrier signal formats. The algorithm is implemented in the time-domain which enables one to use the Gaussian approximation of the transmitted OFDM samples. Consequently the averaging process of the nonpilot data symbols becomes analytically possible resulting in a feasible and computationally efficient channel estimation algorithm leading to a receiver structure that yields also an equalized output from which the data symbols are detected with excellent symbol error rate (SER) performance. Based on this Gaussian approximation the exact Bayesian Cramer Rao lower bound (CRLB) as well as the convergence rate of the algorithm are derived analytically. To reduce the computational complexity of the algorithm discrete Legendre orthogonal basis functions are employed to represent the rapidly time-varying fading channel. It is shown that depending on the normalized Doppler frequency only a small number of expansion coefficients is sufficient to approximate the channel very well and there is no need to know the correlation function of the input signal. The computational complexity of the algorithm is shown to be similar to O(NL) per detected data symbol and per SAGE-MAP algorithm cycle where N is the number of OFDM subcarriers and L is the number of multipath components.
Citation - WoS: 1
Citation - Scopus: 1
Optimal Power Allocation Between Training and Data for Mimo Two-Way Relay Channels
(IEEE-INST Electrical Electronics Engineers Inc, 2015) Li, Xiaofeng; Şenol, Habib; Tepedelenlioğlu, Cihan; Şenol, Habib; Computer Engineering
Power allocation between training and data in MIMO two-way relay systems is proposed which takes into consideration both the symmetric and asymmetric cases of the two sources. For the former we present a closed form for the optimal ratio of data energy to total energy which is suitable for the single antenna case as well and can be simplified when the number of antennas is large. We also show that the achievable rate is a monotonically increasing function of the data time. Concerning the asymmetric case we prove that the difference of the two SNRs is either a concave or convex function of the energy ratio depending on the imbalance between the two sources. Using this the minimum SNR between the two sources is maximized.
Citation - WoS: 7
Citation - Scopus: 10
Artificial Neural Network Based Estimation of Sparse Multipath Channels in Ofdm Systems
(SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2021-01) Şenol, Habib; Şenol, Habib; Abdur Rehman Bin, Tahir; Özmen, Atilla; Özmen, Atilla; Computer Engineering; Electrical-Electronics Engineering
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.
Citation - Scopus: 18
Channel Estimation for TDS-OFDM Systems in Rapidly Time-Varying Mobile Channels
(Institute of Electrical and Electronics Engineers Inc., 2018) Şenol, Habib; Erküçük, Serhat; Erküçük,S.; Çirpan,H.A.; Computer Engineering; Electrical-Electronics Engineering
This paper explores the performance of time-domain synchronous orthogonal frequency-division multiplexing (TDS-OFDM) systems operated under rapidly time-varying mobile channels. Since a rapidly time-varying channel contains more unknown channel coefficients than the number of observations, the mobile channel can conveniently be modeled with the discrete Legendre polynomial basis expansion model to reduce the number of unknowns. The linear minimum mean square error (LMMSE) estimate can be exploited for channel estimation on inter-block-interference-free received signal samples owing to transmitting pseudo-noise (PN) sequences. In conventional TDS-OFDM systems, the channel estimation performance is limited due to estimating channel responses only from the beginning part of the channel. Therefore, a new system model named "partitioned TDS-OFDM system" is proposed to improve the system performance by inserting multiple PN sequences to the middle and end parts of the channel as well. In addition to providing the reconstruction error performance, Bayesian Cramer-Rao lower bound is derived analytically. Also, the LMMSE-based symbol detection is employed. To alleviate the negative effects of inter-carrier-interference (ICI) occuring in mobile channels, ICI cancellation is applied to enhance the detection performance. The simulation results demonstrate that the proposed TDS-OFDM system is superior to the conventional system and its corresponding performance is able to approach the achievable lower performance bound. © 2018 IEEE.