Scholarlink

<p>This paper presents an optimized OFDM waveform design tailored for high-resolution delay–Doppler target mapping in next-generation sensing applications. Unlike traditional OFDM systems optimized for communication, the proposed design focuses on enhancing sensing accuracy by employing clustered subcarrier allocation, inter-carrier interference (ICI)-aware power optimization, and compressed sensing-based recovery. These strategies collectively suppress sidelobes, improve range and velocity resolution, and enable accurate target localization under dynamic 6G conditions. Simulation results demonstrate that the proposed waveform achieves up to ~ 40% reduction in RMSE for range estimation at 0&#xa0;dB SNR and more than 30% improvement in velocity estimation accuracy compared to a conventional unoptimized OFDM waveform. Moreover, the estimator performance remains within ~ 5–10% of the theoretical Cramér–Rao lower bound at high SNR, confirming the near-optimality of the design. In addition, the approach exhibits scalability with respect to sensing subcarrier allocation, balancing resolution gains against ICI effects.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

OFDM waveform design for enhanced delay–Doppler target mapping

  • 期刊论文

  • 发表日期：

    2026年1月7日

查看全文
  • Kwame Ibwe

摘要

This paper presents an optimized OFDM waveform design tailored for high-resolution delay–Doppler target mapping in next-generation sensing applications. Unlike traditional OFDM systems optimized for communication, the proposed design focuses on enhancing sensing accuracy by employing clustered subcarrier allocation, inter-carrier interference (ICI)-aware power optimization, and compressed sensing-based recovery. These strategies collectively suppress sidelobes, improve range and velocity resolution, and enable accurate target localization under dynamic 6G conditions. Simulation results demonstrate that the proposed waveform achieves up to ~ 40% reduction in RMSE for range estimation at 0 dB SNR and more than 30% improvement in velocity estimation accuracy compared to a conventional unoptimized OFDM waveform. Moreover, the estimator performance remains within ~ 5–10% of the theoretical Cramér–Rao lower bound at high SNR, confirming the near-optimality of the design. In addition, the approach exhibits scalability with respect to sensing subcarrier allocation, balancing resolution gains against ICI effects.