A Compressed Tensor-based Subspace Framework for 2D-DOA and Polarization Estimation

In this article, a compressed tensor-based subspace framework is developed to solve the parameter estimation problem in millimeter wave (mmWave) polarized massive multiple-input multiple-output (MIMO) architectures. In the proposed approach, the array measurement is first stacked into a high-dimensional third-order tensor to capture the tensor gain. Then, the high-dimensional third-order tensor is compressed into a low-dimensional one via a tensor compressive sampling (TCS) framework. Subsequently, the tensor-based signal subspace is achieved by imposing higher-order singular value decomposition (HOSVD) on the compressed tensor. Afterwards, the normalized polarization response vector is calculated exploiting the rotational invariance property. Lastly, two-dimensional (2D) direction-of-arrival (DOA) and polarization estimation are implemented with the help of vector cross-product and least squares (LS) techniques, respectively. By incorporating tensor gain with CS, the developed method computationally economical offers acceptable estimation accuracy. Meanwhile, it's insensitive to the sensor position. Numerical simulations demonstrate the advantages of the designed scheme.

I. Introduction

It's known that 5G/6G aims at high capacity, high frequency band, and high bandwidth. Since millimeter wave (mmWave) has more available spectrum and smaller carrier wavelength, it combined with massive multiple-input multiple-output (MIMO) technique, i.e., mmWave massive MIMO, undoubtedly becomes one of the key enabling technologies [1]. Recently, polarization has gained growing attention in 5G/6G, because it may be the last exploitable resource on space-constrained platforms [2]. Consequently, mmWave polarized massive MIMO brings a promising perspective for 5G/6G. As one of the cornerstones of mmWave polarized massive MIMO architectures, sensor array collects data to sense parameter information about targets, like direction-of-arrival (DOA), for subsequent terminal services. Typically, DOA estimation is a prerequisite for various terminal services in 5G/6G wireless communication systems.