Tucker Decomposition For Rotated Codebook in 3D MIMO System Under Spatially Correlated Channel

TL;DR

This paper introduces a Tucker decomposition-based rotated codebook for 3D MIMO systems that significantly reduces dimensionality and computational complexity while maintaining performance in spatially correlated channels.

Contribution

It proposes a novel Tucker decomposition approach for rotated codebooks in 3D MIMO, enabling efficient handling of large antenna arrays with arbitrary configurations.

Findings

Significant dimension reduction compared to traditional codebooks.

Effective performance across various 3D MIMO configurations.

Reduced computational complexity with a closed-form solution.

Abstract

This correspondence proposes a new rotated codebook for three-dimensional (3D) multi-input-multi-output (MIMO) system under spatially correlated channel. To avoid the problem of high dimensionality led by large antenna array, the rotation matrix in the rotated codebook is proposed to be decomposed by Tucker decomposition into three lowdimensional units, i.e., statistical channel direction information in horizontal and vertical directions respectively, and statistical channel power in the joint horizontal and vertical direction. A closed-form suboptimal solution is provided to reduce the computational complexity in Tucker decomposition. The proposed codebook has a significant dimension reduction from conventional rotated codebooks, and is applicable for 3D MIMO system with arbitrary form of antenna array. Simulation results demonstrate that the proposed codebook works very well for various 3D MIMO systems.