Fast Updating the STBC Decoder Matrices in the Uplink of a Massive MIMO System

TL;DR

This paper introduces a novel algorithm to efficiently update decoding matrices in massive MIMO systems, significantly reducing computational complexity during user entry or exit, and when channel estimates change.

Contribution

The paper presents a new matrix inversion update method using partitioned matrices and the Woodbury identity for fast STBC decoding in dynamic massive MIMO uplinks.

Findings

Reduces decoding matrix update complexity in massive MIMO systems

Effective for dynamic user entry and exit scenarios

Confirmed computational efficiency through evaluations

Abstract

Reducing computational complexity of the modern wireless communication systems such as massive Multiple-Input Multiple-Output (MIMO) configurations is of utmost interest. In this paper, we propose new algorithm that can be used to accelerate matrix inversion in the decoding of space-time block codes (STBC) in the uplink of dynamic massive MIMO systems. A multi-user system in which the base station is equipped with a large number of antennas and each user has two antennas is considered. In addition, users can enter or exit the system dynamically. For a given space-time block coding/decoding scheme the computational complexity of the receiver will be significantly reduced when a user is added to or removed from the system by employing the proposed method. In the proposed scheme, the matrix inversion for zero-forcing (ZF) as well as minimum mean square error (MMSE) decoding is derived from the inverse of a partitioned matrix and the Woodbury matrix identity. Furthermore, the suggested technique can be utilized when the number of users is fixed but the channel estimate changes for a particular user. The mathematical equations for updating the inverse of the decoding matrices are derived and its complexity is compared to the direct way of computing the inverse. Evaluations confirm the effectiveness of the proposed approach.