Return
Efficient Channel Estimator With Angle-Division Multiple Access
DOI:10.1109/TCSI.2018.2869783.png)
Abstract
En 中文
Massive multiple input multiple output (M-MIMO) is an enabling technology of 5G wireless communication. The performance of an M-MIMO system is highly dependent on the speed and accuracy of obtaining the channel-state information. The computational complexity of channel estimation for an M-MIMO system can be reduced by making use of the sparsity of the M-MIMO channel. In this paper, we propose the hardware-efficient channel estimator based on angle-division multiple access for the first time. Preamble, uplink, and downlink training are also implemented. For further hardware-efficiency consideration, optimization regarding quantization and approximation strategies has been discussed. Implementation techniques, such as pipelining and systolic processing, are also employed for hardware regularity. Numerical results and field-programmable gate array implementation have demonstrated the advantages of the proposed channel estimator.
Keywords:
M-MIMO
channel estimation
angle-division multiple access (ADMA)
VLSI
pipelining
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.2
Papers:
9.7K
Citations:
2.2W

