Antenna selection for MIMO system based on pattern recognition

• 作者: Jing Zhu Ping Yang Yue Xiao Zhi Chen
• 来源期刊: 数字通信与网络:英文版
• 学科: 工学
• 关键词: ANTENNA selection K-nearest NEIGHBORS MULTIPLE-INPUT multiple-output Pattern RECOGNITION Support VECTOR machine
• 年，卷（期）: 2019,（1）
• 页码范围: 34-39
• 页数: 6页
• 分类号: TN

摘要

This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR), which is termed as the PR aided Transmission Antenna Selection MIMO (PR-TAS aided MIMO). As the conventional TAS algorithms need to search all possible legitimate antenna subsets, they may impose some redundant calculations. In order to avoid this problem, we employ some pattern recognition methods to carry out the TAS algorithm in this paper. To be specific, two PR algorithms, namely the K-Nearest Neighbor (KNN) algorithm and the Support Vector Machine (SVM) algorithm, are introduced and redesigned to obtain a TAS with lower complexity but higher efficiency. Moreover, in order to improve the performance of the SVM, we propose a new feature extraction of channel matrix for the TAS. Our simulation results show that the proposed KNN and SVM based PR-TAS algorithms are capable of striking a flexible tradeoff between the complexity and the Bit Error Rate (BER), and the new feature can effectively improve the BER performance compared with the conventional feature extraction method.