Low Complexity Joint Channel Estimation and Compression for Massive MIMO Systems

被引:0
|
作者
Aafreen, Rubeena [1 ]
Khan, Mohammed Zafar Ali [1 ]
机构
[1] Indian Inst Technol Hyderabad, Dept Elect Engn, Hyderabad, India
关键词
frequency division duplex; singular value decomposition; channel state information; compression; Fast Fourier Transform;
D O I
10.1109/FNWF58287.2023.10520386
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Massive multi-input-multi-output (MIMO) is a promising technology for the upcoming next generation of wireless communications (6G and beyond). To achieve high performance in Frequency Division Duplexed (FDD) massive MIMO, the downlink channel state information (CSI) needs to be accurately feedback to the transmitter. However, for massive MIMO, as the number of antennas increases, the feedback process involves a huge overhead because of a large number of channel coefficients. We propose a Fast Fourier Transform (FFT) based CSI compression and feedback technique, with the use of a low complexity Singular Value Decomposition (SVD) based reconstruction at the receiver. The simulation results show a lower Normalized Mean Square Error (NMSE), with significantly lower complexity than the existing techniques.
引用
收藏
页数:6
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