arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2211.04064cs.ITeess.SPmath.IT
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基于多信号分类的联合通信感知系统

Multiple Signal Classification Based Joint Communication and Sensing System

Xu Chen, Zhiyong Feng, Zhiqing Wei, Xin Yuan, Ping Zhang, J. Andrew Zhang, Heng Yang

摘要:

联合通信与感知(JCS)技术具有频谱利用率高、能量利用率高等优点,已成为移动网络中一种很有前途的技术。到目前为止,移动JCS网络中流行的基于快速傅里叶变换(FFT)的感知方法是基于网格的,网格间隔决定了分辨率。由于移动网络通常在下行链路(DL)时隙中具有有限的连续OFDM符号,因此感测精度受到有限分辨率的限制,特别是对于速度估计。在本文中,我们提出了一种基于多信号分类(MUSIC)的JCS系统,可以实现更高的传感精度的到达角,距离和速度估计,与传统的基于FFT的JCS方法相比。我们进一步提出了一种JCS信道状态信息(CSI)增强方法,利用JCS的感知结果。最后,我们推导出一个理论下限的感知均方误差(MSE),通过使用扰动分析。仿真结果表明,在感知MSE性能方面,建议基于MUSIC的JCS优于基于FFT的一个超过20 dB。此外,使用所提出的JCS CSI增强方法的通信解调的比特出错率(BER)与使用原始估计的CSI的通信相比显著降低。

英文摘要:

Joint communication and sensing (JCS) has become a promising technology for mobile networks because of its higher spectrum and energy efficiency. Up to now, the prevalent fast Fourier transform (FFT)-based sensing method for mobile JCS networks is on-grid based, and the grid interval determines the resolution. Because the mobile network usually has limited consecutive OFDM symbols in a downlink (DL) time slot, the sensing accuracy is restricted by the limited resolution, especially for velocity estimation. In this paper, we propose a multiple signal classification (MUSIC)-based JCS system that can achieve higher sensing accuracy for the angle of arrival, range, and velocity estimation, compared with the traditional FFT-based JCS method. We further propose a JCS channel state information (CSI) enhancement method by leveraging the JCS sensing results. Finally, we derive a theoretical lower bound for sensing mean square error (MSE) by using perturbation analysis. Simulation results show that in terms of the sensing MSE performance, the proposed MUSIC-based JCS outperforms the FFT-based one by more than 20 dB. Moreover, the bit error rate (BER) of communication demodulation using the proposed JCS CSI enhancement method is significantly reduced compared with communication using the originally estimated CSI.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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