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Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In mm-wave massive Multiple Input Multiple Output (MIMO) systems, in order to further improve the spectral efficiency of hybrid precoding in fully connected structure, an Alternate Minimization based on Gradient Descent (GD-AltMin) hybrid precoding algorithm is proposed. Firstly, the right singular vector of the channel matrix is used to initialize the analog precoding matrix. Secondly, digital and analog precoding matrices are updated by least square criterion and gradient descent method respectively. Then, under the principle of alternating minimization, the digital and analog precoding matrices are updated iteratively until the optimal digital and analog precoding matrices are obtained. Through theoretical analysis and numerical simulation, the spectral efficiency of several classical algorithms are compared under different signal-to-noise-ratio, number of radio frequency links and number of transmitting antennas. The results show that the spectral efficiency of the proposed algorithm is closer to the optimal unconstrained precoding algorithm than alternate minimization algorithm using phase extraction and channel singular value decomposition algorithm, especially when the number of radio frequency links is greater than the number of data streams.

In mm-wave massive Multiple Input Multiple Output (MIMO) systems, in order to further improve the spectral efficiency of hybrid precoding in fully connected structure, an Alternate Minimization based on Gradient Descent (GD-AltMin) hybrid precoding algorithm is proposed. Firstly, the right singular vector of the channel matrix is used to initialize the analog precoding matrix. Secondly, digital and analog precoding matrices are updated by least square criterion and gradient descent method respectively. Then, under the principle of alternating minimization, the digital and analog precoding matrices are updated iteratively until the optimal digital and analog precoding matrices are obtained. Through theoretical analysis and numerical simulation, the spectral efficiency of several classical algorithms are compared under different signal-to-noise-ratio, number of radio frequency links and number of transmitting antennas. The results show that the spectral efficiency of the proposed algorithm is closer to the optimal unconstrained precoding algorithm than alternate minimization algorithm using phase extraction and channel singular value decomposition algorithm, especially when the number of radio frequency links is greater than the number of data streams.

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)