Showing 101 - 120 results of 724 for search '"MIMO"', query time: 0.07s Refine Results
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    Adaptive gradient algorithm for hybrid precoding in mmWave MIMO system by Yu ZHANG, Zhi ZHANG, Xiaodai DONG

    Published 2021-10-01
    “…To reduce the complexity of existing hybrid precoding algorithms based on alternating minimization (AltMin) and online learning via gradient descent with momentum in mmWave MIMO systems, aiming at the single-user scenario, the problem of designing the hybrid precoder was reconsidered and an equivalent single hidden layer neural network was proposed.Under the new architecture, the elements of the digital and analog precoder were equivalent to the connecting weights of a single hidden layer neural network, and their optimal solution could be obtained via the weights training method.Inspired by the back propagation (BP) algorithm in feed forward neural networks, an adaptive gradient (AG)-based BP algorithm for hybrid precoding was proposed.Furthermore, the proposed algorithm was extended to the multi-user scenario.The numerical results show that the proposed algorithm achieves approximately the same spectral efficiency as the fully-digital precoding in both the single-user and multi-user scenarios, while has lower complexity than the existing AltMin-based hybrid precoding algorithms and online learning hybrid precoding based on gradient descent with momentum.…”
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    Performance emulation and test for 5G massive MIMO base station by Xiaolong LIU, Guiming WEI, Xiang ZHANG, Yuxin REN, Jiamo JIANG

    Published 2020-06-01
    “…The new radio (NR) of 5G has gathered three main application scenarios and has broken the restrict of the air interface transmission,laying a solid foundation of the information science.Massive MIMO based base station (MMBS) has become the important fulcrum in the implementation deployment of 5G networks.In order to determine performance of the MMBS in sub 6 GHz band,the physical (PHY) layer techniques were firstly introduced,then,for providing a benchmark of the MMBS products,the evaluation method for upbound of the PHY performance and the PHY performance under the fast fading channel environment was given.Based on that,the current mainstream MMBS performance testing methods were analyzed,and a performance testing scheme was proposed which had been suitable for current commercial version of the MMBS.The proposed scheme can be used to test the function and performance of the products with 5G technique.By the end of 2019,there are many manufacturers of MMBS products have been tested by this solution.…”
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  6. 106

    Coordinated Beamforming with Altruistic Precoding and User Selection for MU-MIMO System by Gaofeng Cui, Yanjie Dong, Weidong Wang, Yinghai Zhang

    Published 2014-01-01
    “…Other cell interference (OCI) degrades the achievable capacity of downlink multiuser multiple-input multiple-output (MU-MIMO) systems seriously. Among OCI mitigation schemes, methods that sacrifice ξ degrees of freedom to nullify the OCI have been proven to be helpful to improve the cell edge throughput. …”
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  7. 107

    Pilot interference mitigation for TDD cell-free massive MIMO systems by Yue WANG, Fangmin XU, Haiyan CAO

    Published 2022-05-01
    Subjects: “…cell-free massive MIMO…”
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    SCWOMP Recovery Algorithm for 5G MIMO Communication Symbol Detection by Tao Fu, Yanfeng Yu, Cheng Liu

    Published 2023-01-01
    “…First, the sparseness of MIMO system technology and its transmission structure is analyzed. …”
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    Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix by Gao Xi jun, Chen Zi li, Hu Yong Jiang

    Published 2014-01-01
    “…This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.…”
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    Indoor Massive MIMO Channel Modelling Using Ray-Launching Simulation by Jialai Weng, Xiaoming Tu, Zhihua Lai, Sana Salous, Jie Zhang

    Published 2014-01-01
    “…Massive multi-input multioutput (MIMO) is a promising technique for the next generation of wireless communication networks. …”
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  16. 116

    CSI feedback algorithm based on deep unfolding for massive MIMO systems by Yong LIAO, Gang CHENG, Yujie LI

    Published 2022-12-01
    “…In order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one was approximate message delivery (AMP) algorithm based on learnable parameters.The learnable parameters in deep learning were used to replace the threshold value of the threshold function in the AMP algorithm and the parameters of the Onsage correction term.The nonlinear ability of threshold function in dealing with non-strict sparse data was enhanced.The other was the AMP algorithm based on convolutional network, which replaced the threshold function module with the convolutional residual learning module, and used the module to remove the Gaussian random noise generated by each iteration of the AMP algorithm.Simulation results show that the proposed two algorithms have better CSI feedback performance than AMP algorithm, and the AMP algorithm based on convolutional network has better CSI reconstruction performance than the representative method based on deep learning.…”
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    Dynamic Beamforming for Three-Dimensional MIMO Technique in LTE-Advanced Networks by Yan Li, Xiaodong Ji, Dong Liang, Yuan Li

    Published 2013-01-01
    “…MIMO system with large number of antennas, referred to as large MIMO or massive MIMO, has drawn increased attention as they enable significant throughput and coverage improvement in LTE-Advanced networks. …”
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    A Novel Metamaterial MIMO Antenna with High Isolation for WLAN Applications by Nguyen Khac Kiem, Huynh Nguyen Bao Phuong, Quang Ngoc Hieu, Dao Ngoc Chien

    Published 2015-01-01
    “…A compact 2×2 metamaterial-MIMO antenna for WLAN applications is presented in this paper. …”
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