Yupeng Zheng

—The application of symbol-level precoding (SLP) in intelligent reflecting surface (IRS) aided multiuser multiple-input single-output (MU-MISO) systems faces two main challenges. First, the state-of-the-art joint IRS and SLP optimization approach requires exhaustive enumeration of all possible transmit symbol combinations, resulting in scalability issues as the modulation order and number of users increase. Second, conventional quadrature amplitude modulation (QAM) exhibits strict constructive interference (CI) regions, limiting its effectiveness for CI exploitation in SLP. To address these challenges, this paper proposes a novel modulation scheme, termed hybrid-constellation modulation (HCM), which has a structure of superposed QAM and ASK sub-constellations (SCs). HCM extends the CI regions compared to QAM. Additionally, a two-stage IRS and SLP optimization method is developed to support HCM. The proposed methods are designed for practical IRS with discrete phase shifts and has good scalability. Simulation results show that HCM achieves up to 1.5 dB and 1 dB SER gain over QAM for 16-ary and 64-ary modulation, respectively.