Blind Source Separation For Full-Duplex Systems: Potential and Challenges
Blind Source Separation For Full-Duplex Systems: Potential and Challenges
复制标题
DOI：
10.1109/ojcoms.2021.3086105
复制
发表时间：
2021
影响因子：
7.9
通讯作者：
M. Fouda;Chung-An Shen;Ahmed M. Eltawil
中科院分区：
文献类型：
--
作者：
M. Fouda;Chung-An Shen;Ahmed M. Eltawil
同时发射和接收的全双工通信系统由于在同一节点上发射信号和较弱接收信号的混合而遭受自干扰。在多输入多输出（MIMO）系统中，这个问题变得更加复杂，其中相当大的开销用于训练。在本文中，我们讨论了使用盲源分离技术，即独立分量分析（ICA）来减少MIMO带内全双工无线通信系统的训练开销。讨论了实际限制，并给出了与传统最小二乘方法比较的实验结果，显示了ICA的优势，特别是在低信噪比的情况下。
Full-duplex communications systems that transmit and receive simultaneously suffer self-interference due to the mixing of the transmitted signal and the weaker received signal at the same node. The problem becomes compounded in Multi-Input Multi-Output (MIMO) systems, where considerable overhead is dedicated to training. In this article, we discuss using blind source separation techniques, namely Independent Component Analysis (ICA) to reduce training overhead in MIMO in-band full-duplex wireless communication systems. Practical limitations are discussed and experimental results that compare ICA to traditional Least Square approaches are presented, showing the superiority of ICA, especially in low SNR regimes.