Novel CSI-Free Symbol-Level Precoding for MU-MIMO Systems with MLD Receiver

In this work, we explore symbol-level precoding (SLP) and efficient decoding strategies for downlink transmission in multi-user multiple-input multiple-output (MU-MIMO) systems. We specifically study scenarios where the base station (BS) sends multiple multi-level modulated data streams to users for decoding. We formulate an optimization problem for joint symbollevel transmit precoding and receive combining. However, the receive combining matrix is dependent on the transmit symbols in the joint design scheme, thus, we employ maximum likelihood detection (MLD) method at the receiver side. we demonstrate that the smallest singular value of the precoding matrix significantly affects the MLD performance, while traditional SLP scheme returns a rank-one precoding matrix, which results in inferior error-rate performance to users. To overcome this challenge, we propose a novel channel state information (CSI)-Free SLP scheme that employs semidefinite programming (SDP) method to enable SLP technique in systems utilizing MLD decoding, where the design of the precoding matrix depends only on the modulated data symbols. Numerical simulations confirm that our proposed scheme substantially outperforms the traditional block diagonalization methods.