期刊论文详细信息
Sensors
Self-Interference Channel Training for Full-Duplex Massive MIMO Systems
Taehyoung Kim1  Sangjoon Park2  Kyungsik Min3 
[1]Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea
[2]Department of Electronic Engineering, Kyonggi University, Suwon 16227, Korea
[3]Samsung Electronics Company Ltd., Suwon 16677, Korea
关键词: full-duplex;    massive MIMO;    self-interference;    channel estimation;    partial training;   
DOI  :  10.3390/s21093250
来源: DOAJ
【 摘 要 】
Full-duplex (FD) is a promising technology for increasing the spectral efficiency of next-generation wireless communication systems. A major technical challenge in enabling FD in a real network is to remove the self-interference (SI) caused by simultaneous transmission and reception at the transceiver, and the SI cancellation performance depends significantly on the estimation accuracy of the SI channel. In this study, we proposed a novel partial SI channel training method for minimizing the residual SI power for FD massive multiple-input multiple-output (MIMO) systems. Based on an SI channel training framework under a limited training overhead, using the proposed scheme, the BS estimates only a part of the SI channel vectors, while skipping the channel training for the other remaining SI channel vectors by using their last estimates. With this partial training framework, the proposed scheme finds the optimal partial SI channel training strategy for pilot allocation to minimize the expected residual SI power, considering the time-varying Rician fading channel model for the SI channel. Therefore, the proposed scheme can improve the sum-rate performance compared with other simple partial training schemes for FD massive MIMO systems under a limited training overhead. Numerical results confirm the effectiveness of the proposed scheme for FD massive MIMO systems compared with the full training scheme, as well as other partial training schemes.
【 授权许可】

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