Browsing by Author "Li, Xiaofeng"

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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: 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: 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.
Preface
(Institute of Electrical and Electronics Engineers Inc., 2025) Zhang, Shengfang; Zeng, Pingliang; Ren, Zunfeng; Li, Yonghui; Li, Xiaofeng; Zhao, Haiquan; Luo, Yanbin
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.