Geometric mean decomposition based hybrid precoding for mmWave massive MIMO systems

View Researcher II's Other Codes

Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).

Authors Tian Xie, Linglong Dai, Xinyu Gao, Muhammad Zeeshan Shakir, Jianjun Li
Journal/Conference Name China Communications
Paper Category
Paper Abstract Hybrid precoding can reduce the number of required radio frequency (RF) chains in millimeter-Wave (mmWave) massive MIMO systems. However, existing hybrid pre-coding based on singular value decomposition (SVD) requires the complicated bit allocation to match the different signal-to-noise-ratios (SNRs) of different sub-channels. In this paper, we propose a geometric mean decomposition (GMD)-based hybrid precoding to avoid the complicated bit allocation. Specifically, we seek a pair of analog and digital precoders sufficiently close to the unconstrained fully digital GMD precoder. To achieve this, we fix the analog precoder to design the digital precoder, and vice versa. The analog precoder is designed based on the orthogonal matching pursuit (OMP) algorithm, while GMD is used to obtain the digital precoder. Simulations show that the proposed GMD-based hybrid precoding achieves better performance than the conventional SVD-based hybrid precoding with only a slight increase in complexity.
Date of publication 2018
Code Programming Language MATLAB

Copyright Researcher II 2021