Downlink Precoding with Mixed Statistical and Imperfect Instantaneous CSI for Massive MIMO Systems

TL;DR

This paper explores a new downlink transmission approach in massive MIMO systems using a mix of statistical and imperfect instantaneous CSI, proposing precoding methods that improve power efficiency and system capacity.

Contribution

It introduces extended zero-forcing and maximum ratio transmission precoding techniques that leverage statistical CSI to enhance performance in mixed CSI environments.

Findings

Reduced pilot-based channel estimation requirements

Increased system sum rate and user capacity

Validated theoretical analysis with simulations

Abstract

In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero-forcing (eZF) and an extended maximum ratio transmission (eMRT) precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods.