Regularized Zero-Forcing Interference Alignment for the Two-Cell MIMO Interfering Broadcast Channel

TL;DR

This paper introduces a regularized zero-forcing interference alignment method for two-cell MIMO broadcast channels, improving computational efficiency and convergence without sacrificing effectiveness in managing inter-cell and inter-user interference.

Contribution

It proposes a novel regularized ZF-IA scheme that simplifies transceiver design by avoiding iterative weight optimization, enhancing efficiency and convergence.

Findings

The scheme effectively manages inter-cell and inter-user interference.

It converges faster than existing weighted-sum-rate-maximizing methods.

Simulation results confirm the scheme's effectiveness.

Abstract

In this paper, we propose transceiver design strategies for the two-cell multiple-input multiple-output (MIMO) interfering broadcast channel where inter-cell interference (ICI) exists in addition to interuser interference (IUI). We first formulate the generalized zero-forcing interference alignment (ZF-IA) method based on the alignment of IUI and ICI in multi-dimensional subspace. We then devise a minimum weighted-mean-square-error (WMSE) method based on regularizing the precoders and decoders of the generalized ZF-IA scheme. In contrast to the existing weighted-sum-rate-maximizing transceiver, our method does not require an iterative calculation of the optimal weights. Because of this, the proposed scheme, while not designed specifically to maximize the sum rate, is computationally efficient and achieves a faster convergence compared to the known weighted-sum-rate maximizing scheme. Through analysis and simulation, we show the effectiveness of the proposed regularized ZF-IA scheme.