TENSOR-BASED PARAMETER ESTIMATION OF DOUBLE DIRECTIONAL MASSIVE MIMO CHANNEL WITH DUAL-POLARIZED ANTENNAS

被引:0
|
作者
Qian, Cheng [1 ]
Fu, Xiao [2 ]
Sidiropoulos, Nicholas D. [1 ]
Yang, Ye [3 ]
机构
[1] Univ Virginia, Dept Elect & Comp Engn, Charlottesville, VA 22904 USA
[2] Oregon State Univ, Sch Elect Engn & Comp Sci, Corvallis, OR 97331 USA
[3] WN Huawei Co Ltd, Phys Layer & RRM IC Algorithm Dept, Shanghai, Peoples R China
来源
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2018年
关键词
Channel estimation; massive MIMO; dual-polarized array; tensor factorization; harmonic retrieval; MILLIMETER-WAVE SYSTEMS; DECOMPOSITION; IDENTIFIABILITY; MULTIPATH; FREQUENCY; ALGORITHM; ANGLE;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The 3GPP suggests to combine dual polarized (DP) antenna arrays with the double directional (DD) channel model for downlink channel estimation. This combination strikes a good balance between high-capacity communications and parsimonious channel modeling, and also brings limited feedback schemes for downlink channel estimation within reach. However, most existing channel estimation work under the DD model has not considered DP arrays, perhaps because of the complex array manifold and the resulting difficulty in algorithm design. In this paper, we first reveal that the DD channel with DP arrays at the transmitter and receiver can be naturally modeled as a low-rank four-way tensor, and thus the parameters can be effectively estimated via tensor decomposition algorithms. To reduce computational complexity, we show that the problem can be recast as a four-snapshot three-dimensional harmonic retrieval problem, which can be solved using computationally efficient subspace methods. On the theory side, we show that the DD channel with DP arrays is identifiable under very mild conditions, leveraging identifiability of low-rank tensors. Numerical simulations are employed to showcase the effectiveness of our methods.
引用
收藏
页码:3884 / 3888
页数:5
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