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Grid-less Variational Bayesian Channel Estimation for Antenna Array Systems with Low Resolution ADCs
IEEE Transactions on Wireless Communications ( IF 8.9 ) Pub Date : 2020-03-01 , DOI: 10.1109/twc.2019.2954883
Jiang Zhu , Chao-Kai Wen , Jun Tong , Chongbin Xu , Shi Jin

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.

中文翻译:

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

在接收器处采用低分辨率模数转换器 (ADC) 与大型天线阵列已引起毫米波 (mm-wave) 系统的极大兴趣。由于毫米波通道在角度维度上是稀疏的,因此利用该结构可以减少测量次数,同时实现可接受的性能。受将角度视为随机参数的变分贝叶斯线谱估计 (VALSE) 算法的推动,与先前将估计限制在网格角度点集并导致网格失配的工作相比,本文提出了无网格量化变分用于具有低分辨率 ADC 的天线阵列系统的贝叶斯信道估计 (GL-QVBCE) 算法。
更新日期:2020-03-01
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