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Yue Rong - One of the best experts on this subject based on the ideXlab platform.

  • Transceiver Design for Interference MIMO Relay Systems With Direct Links
    IEEE Transactions on Vehicular Technology, 2017
    Co-Authors: Xinrui Huang, Jianzhou Zhong, Yue Rong
    Abstract:

    In this paper, we consider interference multiple-input multiple-output (MIMO) relay systems where multiple pairs of transmitters–receivers simultaneously communicate through a single relay node and where all nodes are equipped with multiple antennas. We propose a new iterative algorithm to jointly optimize the relay Precoding Matrix and the receiver matrices of such a system based on the minimum sum mean-squared error (MSE) criterion. The optimal structure of the relay Precoding Matrix is developed to decrease the computational complexity of transceiver optimization. Simulation results demonstrate that the proposed transceiver optimization algorithm has a better MSE and bit-error-rate (BER) performance and a faster convergence rate than existing works.

  • Tomlinson-Harashima Precoding Based Transceiver Design for MIMO Relay Systems With Channel Covariance Information
    IEEE Transactions on Wireless Communications, 2015
    Co-Authors: Lenin Gopal, Yue Rong, Zhuquan Zang
    Abstract:

    In this paper, we investigate the performance of the Tomlinson-Harashima (TH) precoder based nonlinear transceiver design for a nonregenerative multiple-input multiple-output (MIMO) relay system assuming that the full channel state information (CSI) of the source-relay link is known, while only the channel covariance information (CCI) of the relay-destination link is available at the relay node. We first derive the structure of the optimal TH Precoding Matrix and the source Precoding Matrix that minimize the mean-squared error (MSE) of the signal waveform estimation at the destination. Then we develop an iterative algorithm to optimize the relay Precoding Matrix. To reduce the computational complexity of the iterative algorithm, we propose a simplified Precoding matrices design scheme. Numerical results show that the proposed Precoding matrices design schemes have a better bit-error-rate performance than existing algorithms.

  • Joint source and relay design for two-hop amplify-and-forward relay networks with QoS constraints
    EURASIP Journal on Wireless Communications and Networking, 2013
    Co-Authors: Jafar Mohammadi, Yue Rong, Feifei Gao, Wen Chen
    Abstract:

    In this paper, we consider the joint design of source Precoding Matrix and the relay Precoding Matrix in a two-hop multiple-input multiple-output relay network. The goal is to find a pair of matrices in order to minimize the power consumption and at the same time meet pre-selected quality of service constraints that are defined as the mean square error of each data stream. Using majorization theory, we simplify the Matrix-valued optimization problem into a scalar-valued one. We then propose a lower bound and an upper bound of the original problem, both in convex forms. Specifically, the latter is solved by a multi-level water-filling algorithm that is much efficient than directly applying the interior point method. Numerical examples corroborate the proposed studies and also demonstrate the tightness of both bounds to the original problem.

  • Joint Source and Relay Optimization for Parallel MIMO Relay Networks
    EURASIP Journal on Advances in Signal Processing, 2012
    Co-Authors: Apriana Toding, Muhammad R. A. Khandaker, Yue Rong
    Abstract:

    In this article, we study the optimal structure of the source Precoding Matrix and the relay amplifying matrices for multiple-input multiple-output (MIMO) relay communication systems with parallel relay nodes. Two types of receivers are considered at the destination node: (1) The linear minimal mean-squared error (MMSE) receiver; (2) The nonlinear decision feedback equalizer based on the minimal MSE criterion. We show that for both receiver schemes, the optimal source Precoding Matrix and the optimal relay amplifying matrices have a beamforming structure. Using such optimal structure, joint source and relay power loading algorithms are developed to minimize the MSE of the signal waveform estimation at the destination. Compared with existing algorithms for parallel MIMO relay networks, the proposed joint source and relay beamforming algorithms have significant improvement in the system bit-error-rate performance.

  • Optimal joint source and relay beamforming for MIMO relays with direct link
    IEEE Communications Letters, 2010
    Co-Authors: Yue Rong
    Abstract:

    In this letter, we investigate the optimal structure of the source Precoding Matrix and the relay amplifying Matrix for non-regenerative multiple-input multiple-output (MIMO) relay communication systems with the direct source-destination link. We show that both the optimal source Precoding Matrix and the optimal relay amplifying Matrix have a beamforming structure. Based on this structure, an iterative joint source and relay beamforming algorithm is developed to minimize the mean-squared error (MSE) of the signal waveform estimation. Numerical example demonstrates an improved performance of the proposed algorithm.

Zhuquan Zang - One of the best experts on this subject based on the ideXlab platform.

  • Tomlinson-Harashima Precoding Based Transceiver Design for MIMO Relay Systems With Channel Covariance Information
    IEEE Transactions on Wireless Communications, 2015
    Co-Authors: Lenin Gopal, Yue Rong, Zhuquan Zang
    Abstract:

    In this paper, we investigate the performance of the Tomlinson-Harashima (TH) precoder based nonlinear transceiver design for a nonregenerative multiple-input multiple-output (MIMO) relay system assuming that the full channel state information (CSI) of the source-relay link is known, while only the channel covariance information (CCI) of the relay-destination link is available at the relay node. We first derive the structure of the optimal TH Precoding Matrix and the source Precoding Matrix that minimize the mean-squared error (MSE) of the signal waveform estimation at the destination. Then we develop an iterative algorithm to optimize the relay Precoding Matrix. To reduce the computational complexity of the iterative algorithm, we propose a simplified Precoding matrices design scheme. Numerical results show that the proposed Precoding matrices design schemes have a better bit-error-rate performance than existing algorithms.

Minjian Zhao - One of the best experts on this subject based on the ideXlab platform.

  • Robust MMSE Precoding Based on Switched Relaying and Side Information for Multiuser MIMO Relay Systems
    IEEE Transactions on Vehicular Technology, 2015
    Co-Authors: Yunlong Cai, Lieliang Yang, Rodrigo C. De Lamare, Minjian Zhao
    Abstract:

    This paper proposes a novel Precoding scheme for multiuser multiple-input–multiple-output (MIMO) relay systems in the presence of imperfect channel state information (CSI). The base station (BS) and the MIMO relay station (RS) are both equipped with the same codebook of unitary matrices. According to each element of the codebook, we create a latent Precoding Matrix pair, namely, a BS Precoding Matrix and an RS Precoding Matrix. The RS Precoding Matrix is formed by multiplying the appropriate unitary Matrix from the codebook by a power scaling factor. Based on the given CSI and a block of transmit symbols, the optimum Precoding Matrix pair, within the class of all possible latent Precoding Matrix pairs derived from the various unitary matrices, is selected by a suitable selection mechanism for transmission, which is designed to minimize the squared Euclidean distance between the pre-estimated received vector and the true transmit symbol vector. We develop a minimum mean-square-error (MMSE) design algorithm to construct the latent Precoding Matrix pairs. In the proposed scheme, rather than sending the complete processing Matrix, only the index of the unitary Matrix and its power scaling factor are sent by the BS to the RS. This significantly reduces the overhead. Simulation results show that, compared with other recently reported Precoding algorithms, the proposed Precoding scheme is capable of providing improved robustness against the effects of CSI estimation errors and multiuser interference.

  • Robust MMSE Precoding for Multiuser MIMO Relay Systems using Switched Relaying and Side Information
    arXiv: Information Theory, 2014
    Co-Authors: Yunlong Cai, Lieliang Yang, Rodrigo C. De Lamare, Minjian Zhao
    Abstract:

    This study proposes a novel Precoding scheme for multiuser multiple-input multiple-output (MIMO) relay systems in the presence of imperfect channel state information (CSI). The base station (BS) and the MIMO relay station (RS) are both equipped with the same codebook of unitary matrices. According to each element of the codebook, we create a latent Precoding Matrix pair, namely a BS Precoding Matrix and an RS Precoding Matrix. The RS Precoding Matrix is formed by multiplying the appropriate unitary Matrix from the codebook by a power scaling factor. Based on the given CSI and a block of transmit symbols, the optimum Precoding Matrix pair, within the class of all possible latent Precoding Matrix pairs derived from the various unitary matrices, is selected by a suitable selection mechanism for transmission, which is designed to minimize the squared Euclidean distance between the pre-estimated received vector and the true transmit symbol vector. We develop a minimum mean square error (MMSE) design algorithm for the construction of the latent Precoding Matrix pairs. In the proposed scheme, rather than sending the complete processing Matrix, only the index of the unitary Matrix and its power scaling factor are sent by the BS to the RS. This significantly reduces the overhead. Simulation results show that compared to other recently reported Precoding algorithms the proposed Precoding scheme is capable of providing improved robustness against the effects of CSI estimation errors and multiuser interference.

M L Honig - One of the best experts on this subject based on the ideXlab platform.

  • capacity of a multiple antenna fading channel with a quantized Precoding Matrix
    IEEE Transactions on Information Theory, 2009
    Co-Authors: Wiroonsak Santipach, M L Honig
    Abstract:

    Given a multiple-input multiple-output (MIMO) channel, feedback from the receiver can be used to specify a transmit Precoding Matrix, which selectively activates the strongest channel modes. Here we analyze the performance of random vector quantization (RVQ), in which the Precoding Matrix is selected from a random codebook containing independent, isotropically distributed entries. We assume that channel elements are independent and identically distributed (i.i.d.) and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using B bits. We first derive the large system capacity of beamforming (rank-one Precoding Matrix) as a function of B, where large system refers to the limit as B and the number of transmit and receive antennas all go to infinity with fixed ratios. RVQ for beamforming is asymptotically optimal, i.e., no other quantization scheme can achieve a larger asymptotic rate. We subsequently consider a Precoding Matrix with arbitrary rank, and approximate the asymptotic RVQ performance with optimal and linear receivers (matched filter and minimum mean squared error (MMSE)). Numerical examples show that these approximations accurately predict the performance of finite-size systems of interest. Given a target spectral efficiency, numerical examples show that the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback.

  • Capacity of a Multiple-Antenna Fading Channel with a Quantized Precoding Matrix
    IEEE Transactions on Information Theory, 2009
    Co-Authors: Wiroonsak Santipach, M L Honig
    Abstract:

    Given a multiple-input multiple-output (MIMO) channel, feedback from the receiver can be used to specify a transmit Precoding Matrix, which selectively activates the strongest channel modes. Here we analyze the performance of Random Vector Quantization (RVQ), in which the Precoding Matrix is selected from a random codebook containing independent, isotropically distributed entries. We assume that channel elements are i.i.d. and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using B bits. We first derive the large system capacity of beamforming (rank-one Precoding Matrix) as a function of B, where large system refers to the limit as B and the number of transmit and receive antennas all go to infinity with fixed ratios. With beamforming RVQ is asymptotically optimal, i.e., no other quantization scheme can achieve a larger asymptotic rate. The performance of RVQ is also compared with that of a simpler reduced-rank scalar quantization scheme in which the beamformer is constrained to lie in a random subspace. We subsequently consider a Precoding Matrix with arbitrary rank, and approximate the asymptotic RVQ performance with optimal and linear receivers (matched filter and Minimum Mean Squared Error (MMSE)). Numerical examples show that these approximations accurately predict the performance of finite-size systems of interest. Given a target spectral efficiency, numerical examples show that the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback.

  • achievable rates for mimo fading channels with limited feedback and linear receivers
    International Symposium on Spread Spectrum Techniques and Applications, 2004
    Co-Authors: Wiroonsak Santipach, M L Honig
    Abstract:

    Channel information at the transmitter can simplify the coding scheme and increase the achievable data rate over a multiple-input multiple-output (MIMO) fading channel. Feed- back from the receiver can be used to specify a Precoding Matrix, which selectively activates the strongest channel modes. We eval- uate the sum data rate per receive antenna when the Precoding Matrix is quantized with a random vector quantization (RVQ) scheme, assuming a matched filter, or linear Minimum Mean Squared Error (MMSE) receiver. Our results are asymptotic as the number of transmit and receive antennas increases with fixed ratio, for a fixed number of feedback bits per dimension. Numerical results show that given a target spectral efficiency, the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback. We also compare these results with a simpler reduced-rank scheme for quantizing the Precoding Matrix.

  • Achievable rates for MIMO fading channels with limited feedback
    Eighth IEEE International Symposium on Spread Spectrum Techniques and Applications - Programme and Book of Abstracts (IEEE Cat. No.04TH8738), 1
    Co-Authors: Wiroonsak Santipach, M L Honig
    Abstract:

    Channel information at the transmitter can simplify the coding scheme and increase the achievable data rate over a multiple-input multiple-output (MIMO) fading channel. Feedback from the receiver can be used to specify a Precoding Matrix, which selectively activates the strongest channel modes. We evaluate the sum data rate per receive antenna when the Precoding Matrix is quantized with a random vector quantization (RVQ) scheme, assuming a matched filter, or linear minimum mean squared error (MMSE) receiver. Our results are asymptotic as the number of transmit and receive antennas increases with fixed ratio, for a fixed number of feedback bits per dimension. Numerical results show that given a target spectral efficiency, the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback. We also compare these results with a simpler reduced-rank scheme for quantizing the Precoding Matrix.

Deming Liu - One of the best experts on this subject based on the ideXlab platform.

  • Investigation of DC-Biased Optical OFDM With Precoding Matrix for Visible Light Communications: Theory, Simulations, and Experiments
    IEEE Photonics Journal, 2018
    Co-Authors: Jiang Tao, Ming Tang, Rui Lin, Zhenhua Feng, Xi Chen, Lei Deng, Wu Liu, Deming Liu
    Abstract:

    Orthogonal frequency-division-multiplexing (OFDM) technology is widely used in visible light communication (VLC) to achieve high data rate transmission. However, the traditional direct-current (DC)-biased optical OFDM (DCO-OFDM) VLC systems suffer from the high peak-to-average power ratio (PAPR) which causes signal clipping distortion, and, thus, performance degradation. Furthermore, severe high-frequency fading due to the limited system bandwidth results in poor bit error rate (BER) performance. Precoding Matrix (PM) techniques have been proposed to enhance the performance of VLC OFDM transmission, but a little or no work has been carried out in investigating the theory of PM used in OFDM VLC systems. In this paper, we aim to reveal the theory of PM-DCO-OFDM for a VLC system. To figure out the intrinsic laws of a PM method, we investigate the principles of PAPR reduction, clipping distortion optimization, and signal-to-noise ratio (SNR) distribution equalization. Based on the analysis of PAPR, we theoretically proved the simplicity of PM as a method to reduce the possibility of high PAPR by improving the autocorrelation performance of input symbols. The clipping distortion could be improved due to the reduction of high PAPR. Moreover, the relatively uniform SNR distribution can be achieved by PM through equalizing the clipping and channel noise, which is beneficial to improve the BER performance in high-frequency constrained systems. However, the PM method used in a DCO-OFDM VLC system should consider the transmitting power, modulation format, and transmission distance as a whole to achieve the transmission performance improvement. The simulation results demonstrate the complementary cumulative distribution function of PAPR can be reduced ∼3 dB, while the performance of clipping distortion power and clipping error probability are significantly improved. Furthermore, experiment is carried out with results showing that the PM method can improve the BER performance in the case that VLC OFDM transmission has enough transmitting power, but with the low transmitting power, the PM also can damage the BER performance. The simulation and experiment results are consistent with our theoretical analysis.