Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/45

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Citation - WoS: 8
Citation - Scopus: 8
Optimal Training for Residual Self-Interference for Full-Duplex One-Way Relays
(IEEE-INST Electrical Electronics Engineers Inc, 2018) Li, Xiaofeng; Tepedelenlioglu, Cihan; Şenol, Habib
Channel 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.
Citation - WoS: 34
Citation - Scopus: 47
Performance of Distributed Estimation Over Unknown Parallel Fading Channels
(IEEE-INST Electrical Electronics Engineers Inc, 2008) Şenol, Habib; Tepedelenlioglu, Cihan
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: 15
Citation - Scopus: 15
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.
Citation - WoS: 36
Citation - Scopus: 37
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; Panayırcı, Erdal; Poor, H. Vincent
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; Tepedelenlioğlu, Cihan; Şenol, Habib
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: 35
Citation - Scopus: 41
Channel Estimation for Residual Self-Interference in Full-Duplex Amplify-And Two-Way Relays
(IEEE-INST Electrical Electronics Engineers Inc, 2017) Li, Xiaofeng; Tepedelenlioglu, Cihan; Şenol, Habib
Training schemes for full duplex two-way relays are investigated. We propose a novel one-block training scheme with a maximum likelihood estimator to estimate the channels between the nodes as well as the residual self-interference (RSI) channel simultaneously. A quasi-Newton algorithm is used to solve the estimator. As a baseline a multi-block training scheme is also considered. The Cramer-Rao bounds of the one-block and multi-block training schemes are derived. By using the Szego's theorem about Toeplitz matrices we analyze how the channel parameters and transmit powers affect the Fisher information. We show analytically that exploiting the structure arising from the RSI channel increases its Fisher information. Numerical results show the benefits of estimating the RSI channel.
Citation - WoS: 78
Citation - Scopus: 86
Joint Channel Estimation Equalization and Data Detection for Ofdm Systems in the Presence of Very High Mobility
(IEEE-INST Electrical Electronics Engineers Inc, 2010) Panayırcı, Erdal; Şenol, Habib; Poor, H. Vincent
This paper is concerned with the challenging and timely problem of joint channel estimation equalization and data detection for uplink 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 (SAGE) technique which is particularly well suited to multicarrier signal formats leading to a receiver structure that also incorporates interchannel interference (ICI) cancelation. In order to reduce the computational complexity of the algorithm band-limited discrete cosine orthogonal basis functions are employed to represent the rapidly time-varying fading channel by the discrete cosine serial expansion coefficients. It is shown that depending on the normalized Doppler frequency only a small number of expansion coefficients is sufficient to approximate the channel perfectly and there is no need to know the correlation function of the input signal. In this way the resulting reduced dimensional channel coefficients are estimated and the data symbols detected iteratively with tractable complexity. The proposed SAGE joint detection algorithm updates the data sequences serially and the channel parameters are updated in parallel leading to a receiver structure that also incorporates ICI cancelation. Computer simulations show that the cosine transformation represents the time-varying channel very effectively and the proposed algorithm has excellent symbol error rate and channel estimation performance even with a very small number of channel expansion coefficients employed in the algorithm resulting in substantial reduction of the computational complexity.

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