Precoding by Pairing Subchannels to Increase MIMO Capacity with Discrete Input Alphabets

TL;DR

This paper introduces a novel precoding method for MIMO channels with discrete inputs, using subchannel pairing and rotation matrices to enhance mutual information while simplifying optimization and detection.

Contribution

It proposes a new pairing-based precoding scheme that improves mutual information in discrete-input MIMO channels and reduces complexity compared to existing methods.

Findings

Achieves mutual information close to the optimal precoder by Cruz et al.

Significantly outperforms Mercury/waterfilling strategy by Lozano et al.

Simplifies precoder optimization and detection for practical use.

Abstract

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non-diagonal precoder based on the X-Codes in \cite{Xcodes_paper} to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using Singular Value Decomposition (SVD) and X-Codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and a $2\times 2$ real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is solved by {\em i}) optimizing the rotation angle and the power allocation within each pair and {\em ii}) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz {\em et al.}, and is significantly better than Mercury/waterfilling strategy by Lozano {\em et al.}. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.