Sidelobe Suppression With Low Peak-to-Valley Power Ratio Waveforms in MIMO-OFDM Dual-Function Radar-Communication Systems

• Published in: IEEE transactions on vehicular technology Vol. 74; no. 4; pp. 5928 - 5940
• Main Authors: Feng, Xiang, Zhao, Zhongqing, Huang, Huiping, Wu, Linlong, Zhao, Zhanfeng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Array signal processing; Communication; Communications systems; Constraints; constructive interference; constructive interference (CI); Discrete Fourier transforms; Dual-functional radar-communication (DFRC); Error reduction; Interference; MIMO communication; Optimization; Orthogonal Frequency Division Multiplexing; Peak to average power ratio; peak-to-valley power ratio; peak-to-valley power ratio (PAPR); Quality of service; Radar; Radar antennas; range sidelobe suppression; Sidelobe reduction; Sidelobes; Symbols; Transforms; Transmission efficiency; Vectors; waveform design; Waveforms
• ISSN: 0018-9545; 1939-9359; 1939-9359
• DOI: 10.1109/TVT.2024.3508077

In orthogonal frequency division multiplexing (OFDM)-based dual-function radar-communication (DFRC) systems, achieving low peak-to-average power ratio (PAPR) is essential for transmission efficiency and performance. Traditional PAPR constraints, however, fall short in managing the dynamic range of waveforms, thereby limiting power maximization. This study introduces a peak-to-valley power ratio (PVPR) constraint for multiple-input multiple-output (MIMO) DFRC systems to enhance hardware compatibility, waveform fidelity, and consistent transmission power. We develop low-PVPR OFDM waveforms tailored for MIMO-DFRC systems, improving both radar and communication functions. For radar applications, we optimize the weighted peak or integrated sidelobe level (WPISL) and employ phase-encoded waveforms to minimize sidelobes. For communication purposes, we implement a constructive interference (CI) design coupled with a waveform similarity error (WSE) constraint. Utilizing the majorization-minimization (MM) framework, we convert the non-convex problem into a series of convex ones. Numerical results demonstrate significant improvements in sidelobe reduction, symbol error rate (SER), and average achievable rate, thereby validating the effectiveness of our approach in enhancing DFRC systems.