College of Physical Science & Engineering, Yichun University, Yichun 336000, China.
Institute of Data Science, City University of Macau, Macau 999078, China.
Sensors (Basel). 2019 Nov 4;19(21):4789. doi: 10.3390/s19214789.
This paper investigates outage probability (OP) performance predictions using transmit antenna selection (TAS) and derives exact closed-form OP expressions for a TAS scheme. It uses Monte-Carlo simulations to evaluate OP performance and verify the analysis. A back-propagation (BP) neural network-based OP performance prediction algorithm is proposed and compared with extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), and BP neural network methods. The proposed method was found to have higher OP performance prediction results than the other prediction methods.
本文研究了利用发射天线选择(TAS)进行中断概率(OP)性能预测,并为 TAS 方案推导出了精确的闭式 OP 表达式。它使用蒙特卡罗模拟来评估 OP 性能并验证分析。提出了一种基于反向传播(BP)神经网络的 OP 性能预测算法,并与极限学习机(ELM)、局部加权线性回归(LWLR)、支持向量机(SVM)和 BP 神经网络方法进行了比较。结果表明,所提出的方法比其他预测方法具有更高的 OP 性能预测结果。