基于DMA阵列划分的低复杂度近场估计方法OA
Low Complexity Near-Field Estimation Method Based on DMA Array Partitioning
针对引入动态超表面天线(Dynamic Metasurface Antenna,DMA)导致近场效应下角度和距离耦合带来计算复杂度提升的问题,提出一种基于DMA阵列划分的低复杂度近场估计方法.首先,建立DMA阵列结构下的近场接收信号模型;其次,对DMA阵列进行划分以构造适合GESPRIT算法的阵列接收信号结构,解耦角度和距离参数,实现低复杂度的处理方法;最后,调整DMA的相移矩阵,通过最大化信噪比提升DMA阵列的近场估计精度.仿真结果表明,该方法相比2D-MUSIC算法复杂度明显降低,且在信噪比为 0dB 时估计精度性能提升30%.
To address the increasing computational complexity caused by angle and distance coupling under near-field effects due to the introduction of dynamic metasurface antenna(DMA),a low-com-plexity near-field estimation method based on DMA array partitioning is proposed.First,the near-field received signal model under the DMA array structure is established.Then,the DMA array is divided to construct the array receiving signal structure suitable for the GESPRIT algorithm,and the angle and distance parameters are decoupled to realize the low complexity processing method.Final-ly,the phase shift matrix of DMA is adjusted to improve the near-field estimation accuracy of DMA array by maximizing the signal-to-noise ratio.The simulation results show that the complexity of this method is significantly lower than that of 2D-MUSIC algorithm,and the estimation accuracy perform-ance is improved by 30%when the SNR is 0 dB.
王雪纯;黄开枝;许晓明
信息工程大学,河南 郑州 450001
电子信息工程
动态超表面天线近场低复杂度
dynamic metasurface antennasnear-fieldlow complexity
《信息工程大学学报》 2024 (001)
39-44 / 6
嵩山实验室资助项目(221100211300-01);国家重点研发计划资助项目(2022YFB2902202)
评论