Robust Design of Power Minimizing Symbol-Level Precoder under Channel Uncertainty

TL;DR

This paper develops robust symbol-level precoding strategies for multiuser MISO channels with imperfect channel knowledge, minimizing power while ensuring QoS, and compares worst-case and probabilistic models through simulations.

Contribution

It introduces a robust SLP design framework for both spherical and stochastic channel uncertainties, optimizing power efficiency under imperfect CSI.

Findings

Robust precoders effectively reduce transmit power under channel uncertainty.

Trade-offs exist between worst-case and probabilistic robust approaches.

Simulation results demonstrate the proposed methods outperform existing techniques.

Abstract

In this paper, we investigate the downlink transmission of a multiuser multiple-input single-output (MISO) channel under a symbol-level precoding (SLP) scheme, having imperfect channel knowledge at the transmitter. In defining the SLP problem, a general category of constructive interference regions (CIR) called distance preserving CIR (DPCIR) is adopted. In particular, we are interested in the robust SLP design minimizing the total transmit power while satisfying the users' quality-of-service (QoS) requirements. We consider two common models for the channel uncertainty region, namely, norm-bounded spherical and stochastic. For the spherical uncertainty model, a worst-case robust precoder is proposed, while for the stochastic uncertainties, we define a convex optimization problem with probabilistic constraints. We simulate the performance of the proposed robust approaches, and compare them with the existing methods. Through the simulation results, we also show that there is an essential trade-off between the two robust approaches.