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针对非线性信道盲均衡问题,考察了一种基于支持向量机的单输入单输出(SISO)盲均衡算法,该算法利用通信信号的常数模特性,将非线性盲均衡问题转化为非线性支持向量回归问题。在此基础上,本文利用分集技术,将该算法拓展至单输入多输出(SIMO)的情况。对两种算法进行的计算机仿真表明,基于支持向量机的SISO盲均衡算法能够有效地抑制信道中的非线性码间干扰;本文提出新算法由于更好地利用了信道的时空特性,具有剩余平均模误差小的优点。
Aiming at the blind channel equalization problem of nonlinear channel, a single input single output (SISO) blind equalization algorithm based on support vector machine is investigated. The algorithm uses the constant modulus of communication signal to transform the nonlinear blind equalization problem into nonlinear support vector Return to the problem. On this basis, this paper extends the algorithm to single-input multiple-output (SIMO) using diversity techniques. Computer simulations of the two algorithms show that the SISO blind equalization algorithm based on SVM can effectively suppress the nonlinear intersymbol interference in the channel. This paper proposes that the new algorithm, due to the better use of the spatio-temporal characteristics of the channel, has the residual average The advantages of small error.