Integrating massive MIMO and simultaneous wireless information and power transfer (SWIPT) technology over the Rician fading channel is an effective method to achieve green communication under 5G background. This paper investigates system that the base station (BS) transmits both wireless energy and information simultaneously to the users. The users send pilots by utilizing the harvested energy from the BS to estimate the channel state, and then obtain the downlink channel state through the channel’s reciprocity to complete uplink and downlink information transmission. We propose an iterative algorithm to jointly optimize the downlink transmitting power of the BS and the power splitting (PS) ratios for minimizing the sum of transmitting power with uplink and downlink signal-to-interference-plus-noise ratio (SINR) constraints. Simulation results prove that the proposed algorithm outperforms over existing related algorithms in terms of transmitting power.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Downlink-Sum-Power Statistical Minimization for Massive MIMO Enabled SWIPT Systems over Rician Fading Channel


    Contributors:
    Chi, Mingjie (author) / Zhang, Yang (author) / Hao, Peili (author) / Pang, Lihua (author) / Chen, Yijian (author) / Ren, Guangliang (author)


    Publication date :

    2020-11-01


    Size :

    1001944 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Downlink NOMA in Multi-UAV Networks over Bivariate Rician Shadowed Fading Channels

    Tan, Zheng Hui Ernest / Madhukumar, A. S. / Sirigina, Rajendra Prasad et al. | IEEE | 2019



    Threshold-Based Pair Switching Scheme in SWIPT-Enabled Wireless Downlink System

    Guo, Yuan / Skouroumounis, Christodoulos / Krikidis, Ioannis | IEEE | 2021


    Performance Analysis of Massive MIMO Two-Way Relay Systems with SWIPT

    Wang, Jinlong / Zheng, Liming / Ding, Ming et al. | IEEE | 2019