The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Xuejing Zhang - One of the best experts on this subject based on the ideXlab platform.

  • robust sidelobe control via complex coefficient weight vector orthogonal decomposition
    IEEE Transactions on Antennas and Propagation, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Julan Xie
    Abstract:

    This paper presents a new Array Response control algorithm named complex-coefficient weight vector orthogonal decomposition (C2-WORD), and its application to robust sidelobe control and synthesis in the presence of steering vector mismatch. The proposed C2-WORD algorithm is a modified version of the existing WORD approach. We extend WORD by allowing a complex-valued combining coefficient in C2-WORD, and then determine the optimal combining coefficient by maximizing the white noise gain. Moreover, assuming that the steering vector uncertainty is norm-bounded, we further devise a robust C2-WORD algorithm, which is able to precisely control the upper boundary Response level of a sidelobe point as desired. To enhance the practicality of the proposed robust C2-WORD algorithm, we also study how to determine the upper norm boundary of steering vector uncertainty under various mismatch circumstances. By applying the robust C2-WORD algorithm iteratively, a robust sidelobe synthesis approach is developed. Contrary to the existing approaches, the devised robust C2-WORD algorithm offers an analytical expression of weight vector updating and can work starting from an arbitrarily specified weight. Simulation results are presented to validate the effectiveness and good performance of the robust C2-WORD algorithm on sidelobe control and synthesis in the presence of steering vector uncertainties.

  • oparc optimal and precise Array Response control algorithm part i fundamentals
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the problem of how to optimally and precisely control Array Response levels is addressed. By using the concept of the optimal weight vector from the adaptive Array theory and adding virtual interferences one by one, the change rule of the optimal weight vector is found and a new formulation of the weight vector update is thus devised. Then, the issue of how to precisely control the Response level of one single direction is investigated. More specifically, we assign a virtual interference to a direction such that the Response level can be precisely controlled. Moreover, the parameters, such as the interference-to-noise ratio, can be figured out according to the desired level. Additionally, the parameter optimization is carried out to obtain the maximal Array gain. The resulting scheme is called optimal and precise Array Response control (OPARC) in this paper. To understand it better, its properties are given, and its comparison with the existing accurate Array Response control algorithm is provided. Finally, simulation results are presented to verify the effectiveness and superiority of the proposed OPARC.

  • oparc optimal and precise Array Response control algorithm part ii multi points and applications
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the optimal and precise Array Response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the Array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to Array signal processing are studied. It is applied to realize Array pattern synthesis (including the general Array case and the large Array case), multi-constraint adaptive beamforming, and quiescent pattern control, where an innovative concept of normalized covariance matrix loading is proposed. Finally, simulation results are presented to validate the effectiveness and good performance of the multi-point OPARC algorithm.

  • pattern synthesis via complex coefficient weight vector orthogonal decomposition part i fundamentals
    arXiv: Signal Processing, 2018
    Co-Authors: Xuejing Zhang, Xuepan Zhang
    Abstract:

    This paper presents a new Array Response control scheme named complex-coefficient weight vector orthogonal decomposition ($ \textrm{C}^2\textrm{-WORD} $) and its application to pattern synthesis. The proposed $ \textrm{C}^2\textrm{-WORD} $ algorithm is a modified version of the existing WORD approach. We extend WORD by allowing a complex-valued combining coefficient in $ \textrm{C}^2\textrm{-WORD} $, and find the optimal combining coefficient by maximizing white noise gain (WNG). Our algorithm offers a closed-from expression to precisely control the Array Response level of a given point starting from an arbitrarily-specified weight vector. In addition, it results less pattern variations on the uncontrolled angles. Elaborate analysis shows that the proposed $ \textrm{C}^2\textrm{-WORD} $ scheme performs at least as good as the state-of-the-art $\textrm{A}^\textrm{2}\textrm{RC} $ or WORD approach. By applying $ \textrm{C}^2\textrm{-WORD} $ successively, we present a flexible and effective approach to pattern synthesis. Numerical examples are provided to demonstrate the flexibility and effectiveness of $ \textrm{C}^2\textrm{-WORD} $ in Array Response control as well as pattern synthesis.

  • pattern synthesis via complex coefficient weight vector orthogonal decomposition part ii robust sidelobe synthesis
    arXiv: Signal Processing, 2018
    Co-Authors: Xuejing Zhang, Xuepan Zhang
    Abstract:

    In this paper, the complex-coefficient weight vector orthogonal decomposition ($ \textrm{C}^2\textrm{-WORD} $) algorithm proposed in Part I of this two paper series is extended to robust sidelobe control and synthesis with steering vector mismatch. Assuming that the steering vector uncertainty is norm-bounded, we obtain the worst-case upper and lower boundaries of Array Response. Then, we devise a robust $ \textrm{C}^2\textrm{-WORD} $ algorithm to control the Response of a sidelobe point by precisely adjusting its upper-boundary Response level as desired. To enhance the practicality of the proposed robust $ \textrm{C}^2\textrm{-WORD} $ algorithm, we also present detailed analyses on how to determine the upper norm boundary of steering vector uncertainty under various mismatch circumstances. By applying the robust $ \textrm{C}^2\textrm{-WORD} $ algorithm iteratively, a robust sidelobe synthesis approach is developed. In this approach, the upper-boundary Response is adjusted in a point-by-point manner by successively updating the weight vector. Contrary to the existing approaches, the devised robust $ \textrm{C}^2\textrm{-WORD} $ algorithm has an analytical expression and can work starting from an arbitrarily-specified weight vector. Simulation results are presented to validate the effectiveness and good performance of the robust $ \textrm{C}^2\textrm{-WORD} $ algorithm.

Xuepan Zhang - One of the best experts on this subject based on the ideXlab platform.

  • robust sidelobe control via complex coefficient weight vector orthogonal decomposition
    IEEE Transactions on Antennas and Propagation, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Julan Xie
    Abstract:

    This paper presents a new Array Response control algorithm named complex-coefficient weight vector orthogonal decomposition (C2-WORD), and its application to robust sidelobe control and synthesis in the presence of steering vector mismatch. The proposed C2-WORD algorithm is a modified version of the existing WORD approach. We extend WORD by allowing a complex-valued combining coefficient in C2-WORD, and then determine the optimal combining coefficient by maximizing the white noise gain. Moreover, assuming that the steering vector uncertainty is norm-bounded, we further devise a robust C2-WORD algorithm, which is able to precisely control the upper boundary Response level of a sidelobe point as desired. To enhance the practicality of the proposed robust C2-WORD algorithm, we also study how to determine the upper norm boundary of steering vector uncertainty under various mismatch circumstances. By applying the robust C2-WORD algorithm iteratively, a robust sidelobe synthesis approach is developed. Contrary to the existing approaches, the devised robust C2-WORD algorithm offers an analytical expression of weight vector updating and can work starting from an arbitrarily specified weight. Simulation results are presented to validate the effectiveness and good performance of the robust C2-WORD algorithm on sidelobe control and synthesis in the presence of steering vector uncertainties.

  • oparc optimal and precise Array Response control algorithm part i fundamentals
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the problem of how to optimally and precisely control Array Response levels is addressed. By using the concept of the optimal weight vector from the adaptive Array theory and adding virtual interferences one by one, the change rule of the optimal weight vector is found and a new formulation of the weight vector update is thus devised. Then, the issue of how to precisely control the Response level of one single direction is investigated. More specifically, we assign a virtual interference to a direction such that the Response level can be precisely controlled. Moreover, the parameters, such as the interference-to-noise ratio, can be figured out according to the desired level. Additionally, the parameter optimization is carried out to obtain the maximal Array gain. The resulting scheme is called optimal and precise Array Response control (OPARC) in this paper. To understand it better, its properties are given, and its comparison with the existing accurate Array Response control algorithm is provided. Finally, simulation results are presented to verify the effectiveness and superiority of the proposed OPARC.

  • oparc optimal and precise Array Response control algorithm part ii multi points and applications
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the optimal and precise Array Response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the Array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to Array signal processing are studied. It is applied to realize Array pattern synthesis (including the general Array case and the large Array case), multi-constraint adaptive beamforming, and quiescent pattern control, where an innovative concept of normalized covariance matrix loading is proposed. Finally, simulation results are presented to validate the effectiveness and good performance of the multi-point OPARC algorithm.

  • pattern synthesis via complex coefficient weight vector orthogonal decomposition part i fundamentals
    arXiv: Signal Processing, 2018
    Co-Authors: Xuejing Zhang, Xuepan Zhang
    Abstract:

    This paper presents a new Array Response control scheme named complex-coefficient weight vector orthogonal decomposition ($ \textrm{C}^2\textrm{-WORD} $) and its application to pattern synthesis. The proposed $ \textrm{C}^2\textrm{-WORD} $ algorithm is a modified version of the existing WORD approach. We extend WORD by allowing a complex-valued combining coefficient in $ \textrm{C}^2\textrm{-WORD} $, and find the optimal combining coefficient by maximizing white noise gain (WNG). Our algorithm offers a closed-from expression to precisely control the Array Response level of a given point starting from an arbitrarily-specified weight vector. In addition, it results less pattern variations on the uncontrolled angles. Elaborate analysis shows that the proposed $ \textrm{C}^2\textrm{-WORD} $ scheme performs at least as good as the state-of-the-art $\textrm{A}^\textrm{2}\textrm{RC} $ or WORD approach. By applying $ \textrm{C}^2\textrm{-WORD} $ successively, we present a flexible and effective approach to pattern synthesis. Numerical examples are provided to demonstrate the flexibility and effectiveness of $ \textrm{C}^2\textrm{-WORD} $ in Array Response control as well as pattern synthesis.

  • pattern synthesis via complex coefficient weight vector orthogonal decomposition part ii robust sidelobe synthesis
    arXiv: Signal Processing, 2018
    Co-Authors: Xuejing Zhang, Xuepan Zhang
    Abstract:

    In this paper, the complex-coefficient weight vector orthogonal decomposition ($ \textrm{C}^2\textrm{-WORD} $) algorithm proposed in Part I of this two paper series is extended to robust sidelobe control and synthesis with steering vector mismatch. Assuming that the steering vector uncertainty is norm-bounded, we obtain the worst-case upper and lower boundaries of Array Response. Then, we devise a robust $ \textrm{C}^2\textrm{-WORD} $ algorithm to control the Response of a sidelobe point by precisely adjusting its upper-boundary Response level as desired. To enhance the practicality of the proposed robust $ \textrm{C}^2\textrm{-WORD} $ algorithm, we also present detailed analyses on how to determine the upper norm boundary of steering vector uncertainty under various mismatch circumstances. By applying the robust $ \textrm{C}^2\textrm{-WORD} $ algorithm iteratively, a robust sidelobe synthesis approach is developed. In this approach, the upper-boundary Response is adjusted in a point-by-point manner by successively updating the weight vector. Contrary to the existing approaches, the devised robust $ \textrm{C}^2\textrm{-WORD} $ algorithm has an analytical expression and can work starting from an arbitrarily-specified weight vector. Simulation results are presented to validate the effectiveness and good performance of the robust $ \textrm{C}^2\textrm{-WORD} $ algorithm.

Rui Zhang - One of the best experts on this subject based on the ideXlab platform.

  • millimeter wave mimo with lens antenna Array a new path division multiplexing paradigm
    IEEE Transactions on Communications, 2016
    Co-Authors: Yong Zeng, Rui Zhang
    Abstract:

    Millimeter wave (mmWave) communication is a promising technology for future wireless systems, while one practical challenge is to achieve its large-antenna gains with only limited radio frequency (RF) chains for cost-effective implementation. To this end, we study in this paper a new lens antenna Array enabled mmWave multiple-input multiple-output (MIMO) communication system. We first show that the Array Response of lens antenna Arrays follows a “sinc” function, where the antenna element with the peak Response is determined by the angle of arrival (AoA)/departure (AoD) of the received/transmitted signal. By exploiting this unique property along with the multi-path sparsity of mmWave channels, we propose a novel low-cost and capacity-achieving spatial multiplexing scheme for both narrow-band and wide-band mmWave communications, termed path division multiplexing (PDM) , where parallel data streams are transmitted over different propagation paths with simple per-path processing. We further propose a simple path grouping technique with group-based small-scale MIMO processing to effectively mitigate the inter-stream interference due to similar AoAs/AoDs. Numerical results are provided to compare the performance of the proposed mmWave lens MIMO against the conventional MIMO with uniform planar Arrays (UPAs) and hybrid analog/digital processing. It is shown that the proposed design achieves significant throughput gains as well as complexity and cost reductions, thus leading to a promising new paradigm for mmWave MIMO communications.

  • Millimeter wave MIMO with lens antenna Array: A new path division multiplexing paradigm
    IEEE Transactions on Communications, 2016
    Co-Authors: Yong Zeng, Rui Zhang
    Abstract:

    Millimeter wave (mmWave) communication is a promising technology for 5G cellular systems. To compensate for the severe path loss in mmWave systems, large antenna Arrays are generally used to achieve significant beamforming gains. However, due to the high hardware and power consumption cost associated with radio frequency (RF) chains, it is desirable to achieve the large-antenna gains, but with only limited number of RF chains for mmWave communications. To this end, we study in this paper a new lens antenna Array enabled mmWave MIMO communication system. We first show that the Array Response of the proposed lens antenna Array at the receiver/transmitter follows a "sinc" function, where the antenna with the peak Response is determined by the angle of arrival (AoA)/departure (AoD) of the received/transmitted signal. By exploiting this unique property of lens antenna Arrays along with the multi-path sparsity of mmWave channels, we propose a novel low-cost and capacity-achieving MIMO transmission scheme, termed \emph{orthogonal path division multiplexing (OPDM)}. For channels with insufficiently separated AoAs and/or AoDs, we also propose a simple \emph{path grouping} technique with group-based small-scale MIMO processing to mitigate the inter-path interference. Numerical results are provided to compare the performance of the proposed lens antenna Arrays for mmWave MIMO system against that of conventional Arrays, under different practical setups. It is shown that the proposed system achieves significant throughput gain as well as complexity and hardware cost reduction, both making it an appealing new paradigm for mmWave MIMO communications.

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

  • oparc optimal and precise Array Response control algorithm part i fundamentals
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the problem of how to optimally and precisely control Array Response levels is addressed. By using the concept of the optimal weight vector from the adaptive Array theory and adding virtual interferences one by one, the change rule of the optimal weight vector is found and a new formulation of the weight vector update is thus devised. Then, the issue of how to precisely control the Response level of one single direction is investigated. More specifically, we assign a virtual interference to a direction such that the Response level can be precisely controlled. Moreover, the parameters, such as the interference-to-noise ratio, can be figured out according to the desired level. Additionally, the parameter optimization is carried out to obtain the maximal Array gain. The resulting scheme is called optimal and precise Array Response control (OPARC) in this paper. To understand it better, its properties are given, and its comparison with the existing accurate Array Response control algorithm is provided. Finally, simulation results are presented to verify the effectiveness and superiority of the proposed OPARC.

  • oparc optimal and precise Array Response control algorithm part ii multi points and applications
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the optimal and precise Array Response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the Array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to Array signal processing are studied. It is applied to realize Array pattern synthesis (including the general Array case and the large Array case), multi-constraint adaptive beamforming, and quiescent pattern control, where an innovative concept of normalized covariance matrix loading is proposed. Finally, simulation results are presented to validate the effectiveness and good performance of the multi-point OPARC algorithm.

  • oparc optimal and precise Array Response control algorithm part i fundamentals
    arXiv: Signal Processing, 2017
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the problem of how to optimally and precisely control Array Response levels is addressed. By using the concept of the optimal weight vector from the adaptive Array theory and adding virtual interferences one by one, the change rule of the optimal weight vector is found and a new formulation of the weight vector update is thus devised. Then, the issue of how to precisely control the Response level of one single direction is investigated. More specifically, we assign a virtual interference to a direction such that the Response level can be precisely controlled. Moreover, the parameters, such as, the interference-to-noise ratio (INR), can be figured out according to the desired level. Additionally, the parameter optimization is carried out to obtain the maximal Array gain. The resulting scheme is called optimal and precise Array Response control (OPARC) in this paper. To understand it better, its properties are given, and its comparison with the existing accurate Array Response control ($ {\textrm A}^2\textrm{RC} $) algorithm is provided. Finally, simulation results are presented to verify the effectiveness and superiority of the proposed OPARC.

  • oparc optimal and precise Array Response control algorithm part ii multi points and applications
    arXiv: Signal Processing, 2017
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the optimal and precise Array Response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the Array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to Array signal processing are studied. It is applied to realize Array pattern synthesis (including the general Array case and the large Array case), multi-constraint adaptive beamforming and quiescent pattern control, where an innovative concept of normalized covariance matrix loading (NCL) is proposed. Finally, simulation results are presented to validate the superiority and effectiveness of the multi-point OPARC algorithm.

Bin Liao - One of the best experts on this subject based on the ideXlab platform.

  • oparc optimal and precise Array Response control algorithm part i fundamentals
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the problem of how to optimally and precisely control Array Response levels is addressed. By using the concept of the optimal weight vector from the adaptive Array theory and adding virtual interferences one by one, the change rule of the optimal weight vector is found and a new formulation of the weight vector update is thus devised. Then, the issue of how to precisely control the Response level of one single direction is investigated. More specifically, we assign a virtual interference to a direction such that the Response level can be precisely controlled. Moreover, the parameters, such as the interference-to-noise ratio, can be figured out according to the desired level. Additionally, the parameter optimization is carried out to obtain the maximal Array gain. The resulting scheme is called optimal and precise Array Response control (OPARC) in this paper. To understand it better, its properties are given, and its comparison with the existing accurate Array Response control algorithm is provided. Finally, simulation results are presented to verify the effectiveness and superiority of the proposed OPARC.

  • oparc optimal and precise Array Response control algorithm part ii multi points and applications
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the optimal and precise Array Response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the Array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to Array signal processing are studied. It is applied to realize Array pattern synthesis (including the general Array case and the large Array case), multi-constraint adaptive beamforming, and quiescent pattern control, where an innovative concept of normalized covariance matrix loading is proposed. Finally, simulation results are presented to validate the effectiveness and good performance of the multi-point OPARC algorithm.

  • pattern synthesis for arbitrary Arrays via weight vector orthogonal decomposition
    IEEE Transactions on Signal Processing, 2018
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Zishu He, Bin Liao, Weilai Peng
    Abstract:

    This paper presents a new scheme based on Weight vector ORthogonal Decomposition (WORD) to control the Array Response at a given direction and a novel WORD-based approach to pattern synthesis for arbitrary Arrays. The central concept of the proposed methods stems from the adaptive Array theory. More precisely, it is found that the inverse of the noise-plus-interference covariance matrix in adaptive beamforming can be regarded as a linear combination of two orthogonal projection matrices, and, accordingly, the optimal weight vector is a linear combination of two orthogonal vectors. With such an observation, the WORD scheme is developed to design the desired weight vector. It is shown that the Array Response at a given direction can be precisely adjusted to an arbitrary level, by simply determining appropriate combination coefficients for those two orthogonal vectors. Furthermore, a closed-form expression of the weight vector can be achieved by introducing a new cost function that measures pattern variation. By employing the WORD scheme successively, a novel approach to pattern synthesis for arbitrary Arrays is devised. At each implementation step of this approach, the Array pattern is adjusted in a point-by-point manner by successively modifying the weight vector. As such, both the sidelobe and mainlobe regions can be flexibly synthesized. Numerical examples are provided to demonstrate the effectiveness and flexibility of the WORD scheme in Array Response control at a single direction as well as pattern synthesis.

  • oparc optimal and precise Array Response control algorithm part i fundamentals
    arXiv: Signal Processing, 2017
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the problem of how to optimally and precisely control Array Response levels is addressed. By using the concept of the optimal weight vector from the adaptive Array theory and adding virtual interferences one by one, the change rule of the optimal weight vector is found and a new formulation of the weight vector update is thus devised. Then, the issue of how to precisely control the Response level of one single direction is investigated. More specifically, we assign a virtual interference to a direction such that the Response level can be precisely controlled. Moreover, the parameters, such as, the interference-to-noise ratio (INR), can be figured out according to the desired level. Additionally, the parameter optimization is carried out to obtain the maximal Array gain. The resulting scheme is called optimal and precise Array Response control (OPARC) in this paper. To understand it better, its properties are given, and its comparison with the existing accurate Array Response control ($ {\textrm A}^2\textrm{RC} $) algorithm is provided. Finally, simulation results are presented to verify the effectiveness and superiority of the proposed OPARC.

  • oparc optimal and precise Array Response control algorithm part ii multi points and applications
    arXiv: Signal Processing, 2017
    Co-Authors: Xuejing Zhang, Xuepan Zhang, Bin Liao, Xianggen Xia, Yue Yang
    Abstract:

    In this paper, the optimal and precise Array Response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the Array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to Array signal processing are studied. It is applied to realize Array pattern synthesis (including the general Array case and the large Array case), multi-constraint adaptive beamforming and quiescent pattern control, where an innovative concept of normalized covariance matrix loading (NCL) is proposed. Finally, simulation results are presented to validate the superiority and effectiveness of the multi-point OPARC algorithm.