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作 者:褚宏云 李旭旭 潘雪 李莹华 CHU Hongyun;LI Xuxu;PAN Xue;LI Yinghua(School of Communication and Information Engineering,Xi'an University of Posts and Telecommunications,Xi’an 710121,China)
机构地区:[1]西安邮电大学通信与信息工程学院,陕西西安710121
出 处:《移动通信》2024年第4期81-85,104,共6页Mobile Communications
基 金:陕西省自然科学基金“干扰利用驱动的智能超表面分段信道估计方法研究”(2022JQ-635)。
摘 要:面向未来6G网络,ISAC与XL-MIMO技术有机结合、共同演进,有望进一步提升ISAC性能。然而,XL-MIMO-ISAC中部署大量天线会产生近场效应,为准确获取CSI和目标参数信息带来关键挑战。为此,采用线性修改的原子范数最小化方法,建模毫米波通信信道和感知阵列响应这两种盲源之间极坐标域的子空间一致关联,并提出了一种基于盲超分辨技术的CSI与感知参数并行估计方案,以避免从叠加信号中串行估计通信信道与目标参数信息造成误差传播。将联合盲源估计建模为非完全观测条件下的低秩矩阵重构问题,并引入PSWF将问题转化为SDP。仿真结果验证了提出的算法在CSI精度和目标参数分辨率方面的有效性。For future 6G networks, the organic integration and co-evolution of integrated sensing and communication (ISAC) andextremely large-scale MIMO (XL-MIMO) technologies is expected to further improve ISAC performance through. However,deploying massive antennas in XL-MIMO-ISAC can generate near-field effects, posing a key challenge for accuratelyobtaining channel state information (CSI) and target parameter information. To this end, a linearly modified atomic normminimization method is adopted to model the subspace consistent correlation between the millimeter wave communicationchannel and the sensing array response in the polar coordinate domain. A parallel estimation scheme for CSI and sensingparameters based on blind super-resolution technology is proposed to avoid the error propagation caused by serial estimationof communication channel and target parameter information from superimposed signals. The joint blind source estimation ismodeled as a low-rank matrix reconstruction problem under incomplete observation conditions, and prolate spheroidal wavefunction (PSWF) is introduced to transform the problem into semidefinite programming (SDP). The simulation results verifythe effectiveness of the proposed algorithm in terms of CSI accuracy and target parameter resolution.
关 键 词:通信感知一体化 线性修改的原子范数 近场信道与感知参数估计 椭球体波函数 盲超分辨
分 类 号:TN929.5[电子电信—通信与信息系统]
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