Grid-Less Variational Bayesian Channel Estimation for Antenna Array Systems With Low Resolution ADCs
Grid-Less Variational Bayesian Channel Estimation for Antenna Array Systems With Low Resolution ADCs
复制标题
具有低分辨率 ADC 的天线阵列系统的无网格变分贝叶斯信道估计
DOI：
10.1109/twc.2019.2954883
复制
发表时间：
2020-03-01
影响因子：
10.4
通讯作者：
Jin, Shi
中科院分区：
文献类型：
--
作者：
Zhu, Jiang;Wen, Chao-Kai;Jin, Shi
采用低分辨率模数转换器（adc）与接收机上的大型天线阵列相结合已经引起了人们对毫米波系统的极大兴趣。由于毫米波通道在角尺寸上是稀疏的，利用这种结构可以减少测量次数，同时获得可接受的性能。针对将角度作为随机参数的变分贝叶斯线谱估计（VALSE）算法，本文针对低分辨率adc的天线阵列系统，提出了一种无网格量化变分贝叶斯信道估计（GL-QVBCE）算法。数值计算结果表明，与cramror Rao界（CRB）和现有方法相比，GL-QVBCE具有接近最优的性能。
Employing low-resolution analog-to-digital converters (ADCs) coupled with large antenna arrays at the receivers has drawn considerable interests in the millimeter wave (mm-wave) system. Since mm-wave channels are sparse in angular dimensions, exploiting the structure could reduce the number of measurements while achieving acceptable performance at the same time. Motivated by the variational Bayesian line spectral estimation (VALSE) algorithm which treats the angles as random parameters, in contrast to previous works which confine the estimate to the set of grid angle points and induce grid mismatch, this paper proposes the grid-less quantized variational Bayesian channel estimation (GL-QVBCE) algorithm for antenna array systems with low resolution ADCs. Numerical results show the near optimal performance of GL-QVBCE by comparing with the Cramèr Rao bound (CRB) and the state-of-art methods.