Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation

TL;DR

This paper extends symbol-level precoding to multi-level modulations like MQAM and APSK, proposing algorithms that enhance power efficiency and adapt modulation schemes for improved throughput in multiuser MISO systems.

Contribution

It introduces a novel connection between symbol-level precoding and PHY layer multicasting with phase constraints for multi-level modulations, along with adaptive schemes for power minimization.

Findings

Significant power and energy efficiency improvements achieved.

Adaptive modulation schemes effectively match data rate requirements.

Proposed algorithms outperform existing methods in simulations.

Abstract

Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for MPSK modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. MQAM and APSK by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user SINR or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate.