A New Hybrid Precoding Approach for Multi-user Massive MIMO over Fading Channels

TL;DR

This paper introduces a hybrid precoding method for multi-user massive MIMO systems that models angle and phase as correlated variables, enhancing data transmission efficiency and robustness over fading channels.

Contribution

It presents a novel hybrid precoding approach that incorporates joint angle-phase correlation and entropy modeling, improving sum-rate and robustness in MU-MIMO systems.

Findings

Achieved 18.31% higher sum-rate compared to existing methods.

Improved robustness by 11.47% over state-of-the-art techniques.

Validated analytical models with simulation results.

Abstract

Hybrid precoding is an indispensable technique to harness the full potential of a multi-user massive multiple-input, multiple-output (MU-MMIMO) system. In this paper, we propose a new hybrid precoding approach that combines digital and analog precoding to optimize data transmission over multiple antennas. This approach steers signals in specific directions, leading to maximizing sum-rate and suppressing side-lobe interference. When dealing with complex signals, changes in phase are naturally associated with changes in angle, and these variations are inherently correlated. The correlation between the angle and phase is essential for accurately determining the channel characteristics. An important aspect of this approach is that we model the angle and phase as correlated variables following a bivariate Gaussian distribution, and for the first time, we define a joint angle and phase entropy to measure the uncertainty of angle and phase variations in wireless channels. This entropy is crucial to adapt the proposed precoding method with variations. Simulation result validate the accuracy of our analytical findings, demonstrating 18.31% increase in sum-rate and an 11.47% improvement in robustness compared to other state-of-the-art methods.