YZ

Yupeng Zheng


Postgraduate Research Student in Communication Systems
MSc

About

My research project

Publications

Yupeng Zheng, Ang Li, Jinfei Wang, Yi Ma, Rahim Tafazolli (2026)Low-Complexity Tone Injection via Candidate Ranking for PAPR Reduction in OFDM and AFDM Systems, In: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications 2026 IEEE

—Tone injection (TI) is a promising distortionless PAPR reduction technique that incurs no spectral efficiency loss. However, state-of-the-art TI schemes based on random candidate generation or clipping noise spectrum suffer from fundamental limitations in PAPR performance. In this paper, we propose novel TI schemes compatible with both OFDM and AFDM systems. The proposed schemes iteratively update the TI sequence via a candidate ranking procedure guided by time-domain local peaks. This accurately selects effective candidates while achieving a complexity comparable to that of the fast Fourier transform. Depth-first search is further integrated to enhance PAPR performance by exploiting the tree structure of the process. Simulations demonstrate that the proposed schemes achieve over 1 dB PAPR gain over baseline TI schemes at comparable complexity. The gain is consistent across various numbers of subcarriers under controlled per-iteration complexities, confirming a superior performance-complexity trade-off for both OFDM and AFDM.

Yupeng Zheng, Yi Ma, Rahim Tafazolli (2025)Hybrid Constellation Modulation for Symbol-Level Precoding in IRS-Aided MU-MIMO Systems, In: Pre-print

—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.