Array independent MIMO channel models with analytical characteristics

TL;DR

This paper introduces array independent MIMO channel models that facilitate analytical characterization and capacity prediction, extending existing models to arbitrary array configurations using manifold decomposition.

Contribution

The paper develops array independent MIMO channel models applicable to arbitrary array configurations, extending the virtual channel representation and integrating the Weichselberger model.

Findings

Models accurately estimate angular power spectrum.

Models effectively predict channel capacity.

Array characteristics significantly impact capacity.

Abstract

The conventional analytical channel models for multiple-input multiple-output (MIMO) wireless radio channels are array dependent. In this paper, we present several array independent MIMO channel models that inherit the essence of analytical models. The key idea is to decompose the physical scattering channel into two parts using the manifold decomposition technique: one is the wavefield independent sampling matrices depending on the antenna arrays only; the other is the array independent physical channel that can be individually modeled in an analytical manner. Based on the framework, we firstly extend the conventional virtual channel representation (VCR), which is restricted to uniform linear arrays (ULAs) so far, to a general version applicable to arbitrary array configurations. Then, we present two array independent stochastic MIMO channel models based on the proposed new VCR as well as the Weichselberger model. These two models are good at angular power spectrum (APS) estimation and capacity prediction, respectively. Finally, the impact of array characteristics on channel capacity is separately investigated by studying the condition number of the array steering matrix at fixed angles, and the results agree well with existing conclusions. Numerical results are presented for model validation and comparison.