Chen Xianqing, Wu Lenan
School of Information Science and Engineering, University of Southeast, 2 Sipailou, Nanjing 210096, China.
ScientificWorldJournal. 2012;2012:180469. doi: 10.1100/2012/180469. Epub 2012 Nov 20.
The extended binary phase shift keying (EBPSK) is an efficient modulation technique, and a special impacting filter (SIF) is used in its demodulator to improve the bit error rate (BER) performance. However, the conventional threshold decision cannot achieve the optimum performance, and the SIF brings more difficulty in obtaining the posterior probability for LDPC decoding. In this paper, we concentrate not only on reducing the BER of demodulation, but also on providing accurate posterior probability estimates (PPEs). A new approach for the nonlinear demodulation based on the support vector machine (SVM) classifier is introduced. The SVM method which selects only a few sampling points from the filter output was used for getting PPEs. The simulation results show that the accurate posterior probability can be obtained with this method and the BER performance can be improved significantly by applying LDPC codes. Moreover, we analyzed the effect of getting the posterior probability with different methods and different sampling rates. We show that there are more advantages of the SVM method under bad condition and it is less sensitive to the sampling rate than other methods. Thus, SVM is an effective method for EBPSK demodulation and getting posterior probability for LDPC decoding.
扩展二进制相移键控（EBPSK）是一种高效的调制技术，其解调器中使用了一种特殊的冲击滤波器（SIF）来提高误码率（BER）性能。然而，传统的阈值判决无法实现最佳性能，并且SIF给低密度奇偶校验（LDPC）解码获取后验概率带来了更多困难。在本文中，我们不仅专注于降低解调的误码率，还致力于提供准确的后验概率估计（PPE）。介绍了一种基于支持向量机（SVM）分类器的非线性解调新方法。使用仅从滤波器输出中选择少数采样点的SVM方法来获取PPE。仿真结果表明，该方法能够获得准确的后验概率，并且通过应用LDPC码可以显著提高误码率性能。此外，我们分析了不同方法和不同采样率获取后验概率的效果。我们表明，在恶劣条件下SVM方法具有更多优势，并且它比其他方法对采样率的敏感度更低。因此，SVM是一种用于EBPSK解调以及为LDPC解码获取后验概率的有效方法。
