On one hand, aiming at the prominent problem of improving the reliability of Faster-than-Nyquist (FTN) wireless transmission, abandoning the channel estimation, we propose the Radial Basis Function Least Squares Support Vector Machine (RBF LSSVM) algorithm based on Intelligent Signal Processing for FTN equalization and form FTN time domain transverse filter equalizer. The model of FTN wireless communication system based on equalization of LSSVM algorithm is established by adding 50-bit training sample sequence module. On the other hand, in the FTN transmission BPSK modulation system receiving terminal, we propose joint research equalization of LSSVM algorithm and adaptive channel decoding scheme of Chase algorithm, to improve the reliable transmission performance of FTN wireless communication. The threshold value is 20, and the adaptive 2-D Turbo Product Codes (TPC) encoding and decoding is simulated by four iterations. The BER performance of FTN wireless communication combined with LSSVM algorithm and TPC adaptive decoding is simulated.

中文翻译：

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快于奈奎斯特接收机中基于RBF LSSVM和自适应信道解码的智能均衡

一方面，针对提高快于奈奎斯特（FTN）无线传输可靠性的突出问题，摒弃信道估计，提出基于智能信号的径向基函数最小二乘支持向量机（RBF LSSVM）算法。处理FTN均衡，形成FTN时域横向滤波器均衡器。通过增加50位训练样本序列模块，建立了基于LSSVM算法均衡的FTN无线通信系统模型。另一方面，在FTN传输BPSK调制系统接收端，我们提出联合研究LSSVM算法的均衡和Chase算法的自适应信道解码方案，以提高FTN无线通信的可靠传输性能。阈值为 20，自适应二维 Turbo 乘积码 (TPC) 编码和解码通过四次迭代来模拟。仿真了结合LSSVM算法和TPC自适应解码的FTN无线通信BER性能。