A Hierarchical Rate Splitting Strategy for FDD Massive MIMO under Imperfect CSIT

TL;DR

This paper introduces a Hierarchical Rate Splitting strategy for FDD massive MIMO systems that improves sum rate performance under imperfect CSIT by transmitting multiple types of common messages and optimizing power allocation.

Contribution

The paper proposes a novel Hierarchical Rate Splitting framework tailored for FDD massive MIMO, enhancing interference management and sum rate under imperfect CSIT.

Findings

HRS achieves significant sum rate gains over baselines.

Closed-form power allocation provides system insights.

Asymptotic analysis validates HRS effectiveness.

Abstract

In a multiuser MIMO broadcast channel, the rate performance is affected by the multiuser interference when the Channel State Information at the Transmitter (CSIT) is imperfect. To tackle the interference problem, a Rate-Splitting (RS) approach has been proposed recently, which splits one user's message into a common and a private part, and superimposes the common message on top of the private messages. The common message is drawn from a public codebook and should be decoded by all users. In this paper, we propose a novel and general framework, denoted as Hierarchical Rate Splitting (HRS), that is particularly suited to FDD massive MIMO systems. HRS simultaneously transmits private messages intended to each user and two kinds of common messages that can be decoded by all users and by a subset of users, respectively. We analyse the asymptotic sum rate of HRS under imperfect CSIT. A closed-form power allocation is derived which provides insights into the effects of system parameters. Finally, simulation results validate the significant sum rate gain of HRS over various baselines.