融合CHIRP与OFDM的ISAC波形
Amalgamated CHIRP and OFDM for ISAC
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中文总结 AI 辅助
本文提出了一种融合CHIRP与OFDM的ISAC波形，通过仿射相加减少PAPR并提升通信与感知性能。
中文摘要 AI 辅助
集成感知与通信（ISAC）需要开发一种能够高效支持通信和感知功能的波形。本文提出了一种新的波形，结合正交频分复用（OFDM）和CHIRP波形的优点，以在ISAC框架内提高通信和感知性能。因此，提出了一种新的架构，利用传统的通信框架，同时利用接收端（Rx）感知的参数来增强通信性能。我们证明了OFDM和CHIRP信号的仿射相加会产生近常包络的OFDM波形，这有效降低了峰值对平均功率比（PAPR），这是传统OFDM系统的关键限制。使用传统方式在OFDM框架中进行感知需要分配一些资源用于感知，这会降低通信性能。为了解决这个问题，所提出的仿射融合通过CHIRP波形进行感知，而无需消耗通信资源，从而保持通信效率。此外，提出了一种在槽级将CHIRP信号整合到OFDM框架中的新技术，以提高距离估计的准确性。结果表明，与CHIRP结合的OFDM信号具有更好的自相关特性，改进了距离和速度的均方根误差（RMSE），并且PAPR更低。最后，我们characterized通信和感知性能之间的权衡。
英文摘要
Integrated Sensing and Communication (ISAC) requires the development of a waveform capable of efficiently supporting both communication and sensing functionalities. This paper proposes a novel waveform that combines the benefits of both the orthogonal frequency division multiplexing (OFDM) and the chirp waveforms to improve both the communication and sensing performance within an ISAC framework. Hence, a new architecture is proposed that utilizes the conventional communication framework while leveraging the parameters sensed at the receiver (Rx) for enhancing the communication performance. We demonstrate that the affine addition of OFDM and chirp signals results in a near constant-envelope OFDM waveform, which effectively reduces the peak-to-average power ratio (PAPR), a key limitation of traditional OFDM systems. Using the OFDM framework for sensing in the conventional fashion requires the allocation of some resources for sensing, which in turn reduces communication performance. As a remedy, the proposed affine amalgam facilitates sensing through the chirp waveform without consuming communication resources, thereby preserving communication efficiency. Furthermore, a novel technique of integrating the chirp signal into the OFDM framework at the slot-level is proposed to enhance the accuracy of range estimation. The results show that the OFDM signal incorporated with chirp has better autocorrelation properties, improved root mean square error (RMSE) of range and velocity, and lower PAPR. Finally, we characterize the trade-off between communications and sensing performance.
