arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2211.04063cs.ITcs.ETmath.IT
收藏

联合通信与感知中的感知辅助上行信道估计

Sensing-aided Uplink Channel Estimation for Joint Communication and Sensing

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

摘要:

联合通信与感知(JCAS)技术由于其使用相同的发送信号进行通信和感知的高频谱效率而引起了人们的极大关注。利用上行信道与感知结果的相关性,提出了一种基于感知辅助卡尔曼滤波器(SAKF)的上行JCAS信道状态信息(CSI)估计方法,利用到达角(AoA)估计提高CSI估计精度。提出了一种基于卡尔曼滤波器(KF)的信道状态信息(CSI)增强方法,该方法利用所估计的AoA作为先验信息来改进最小二乘CSI估计。仿真结果表明,基于SAKF的信道状态信息估计方法的出错率(BER)接近最小均方误差(MMSE)方法,而复杂度显著降低。

英文摘要:

The joint communication and sensing (JCAS) technique has drawn great attention due to its high spectrum efficiency by using the same transmit signal for both communication and sensing. Exploiting the correlation between the uplink (UL) channel and the sensing results, we propose a sensing-aided Kalman filter (SAKF)-based channel state information (CSI) estimation method for UL JCAS, which exploits the angle-of-arrival (AoA) estimation to improve the CSI estimation accuracy. A Kalman filter (KF)-based CSI enhancement method is proposed to refine the least-square CSI estimation by exploiting the estimated AoA as the prior information. Simulation results show that the bit error rates (BER) of UL communication using the proposed SAKF-based CSI estimation method approach those using the minimum mean square error (MMSE) method, while at significantly reduced complexity.

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。

↑