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5G QC-LDPC 编码短包全双工传输中的联合半盲自干扰消除和均衡处理。

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions.

机构信息

Univ Brest, CNRS, Lab-STICC, CS 93837, 6 Avenue Le Gorgeu, CEDEX 3, 29238 Brest, France.

School of Electrical Engineering, International University, Ho Chi Minh City 700000, Vietnam.

出版信息

Sensors (Basel). 2022 Mar 11;22(6):2204. doi: 10.3390/s22062204.

DOI:10.3390/s22062204
PMID:35336375
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8949082/
Abstract

The paper proposes a joint semi-blind algorithm for simultaneously cancelling the self-interference component and estimating the propagation channel in 5G Quasi-Cyclic Low-Density Parity-Check (QC-LDPC)-encoded short-packet Full-Duplex (FD) transmissions. To avoid the effect of channel estimation processes when using short-packet transmissions, this semi-blind algorithm was developed by taking into account only a small number (four at least) pilot symbols, which was integrated with the intended information sequence and used for the feedback loop of the estimation of the channels. The results showed that this semi-blind algorithm not only achieved nearly optimal performance, but also significantly reduced the processing time and computational complexity. This semi-blind algorithm can also improve the performances of the Mean-Squared Error (MSE) and Bit Error Rate (BER). The results of this study highlight the potential efficiency of this joint semi-blind iterative algorithm for 5G and Beyond and/or practical IoT transmission scenarios.

摘要

本文提出了一种联合半盲算法，用于在 5G 准循环低密度奇偶校验（QC-LDPC）编码的短包全双工（FD）传输中同时消除自干扰分量和估计传播信道。为了避免在使用短包传输时信道估计过程的影响，该半盲算法仅考虑了少量（至少四个）导频符号，这些符号与预期的信息序列一起被集成，并用于信道估计的反馈回路。结果表明，该半盲算法不仅实现了几乎最优的性能，而且显著降低了处理时间和计算复杂度。该半盲算法还可以提高均方误差（MSE）和误码率（BER）的性能。本研究的结果突出了这种联合半盲迭代算法在 5G 及以后和/或实际物联网传输场景中的潜在效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e99/8949082/deb655d40240/sensors-22-02204-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e99/8949082/9ece94d22809/sensors-22-02204-g005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e99/8949082/c67719bb36f1/sensors-22-02204-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e99/8949082/8ac2932dbe60/sensors-22-02204-g009.jpg
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