Efficient Channel Estimator with Angle-Division Multiple Access
Xiaozhen Liu (1), Jin Sha (1), Hongxiang Xie (2), Feifei Gao (2), Shi, Jin (5), Zaichen Zhang (4, 5), Xiaohu You (5), Chuan Zhang (3, 4, 5), ((1) School of Electronic Science, Engineering, Nanjing University, China,, (2) Department of Automation, Tsinghua University, Beijing

TL;DR
This paper introduces a hardware-efficient channel estimator for massive MIMO systems using angle-division multiple access, enhancing speed and accuracy of channel state information with FPGA implementation.
Contribution
It proposes the first hardware-efficient ADMA-based channel estimator with optimized quantization, pipelining, and systolic processing techniques.
Findings
Numerical results show improved estimation accuracy.
FPGA implementation demonstrates hardware efficiency.
The method reduces computational complexity of M-MIMO channel estimation.
Abstract
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 (CSI). 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 (ADMA) for the first time. Preamble, uplink (UL) and downlink (DL) training are also implemented. For further hardware-efficiency consideration, optimization regarding quantization and approximation strategies have been discussed. Implementation techniques such as pipelining and systolic processing are also employed for hardware regularity. Numerical results and FPGA implementation have demonstrated the…
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Taxonomy
TopicsAdvanced Wireless Communication Techniques · Advanced MIMO Systems Optimization · Wireless Communication Networks Research
