为解决EBPSK信号使用经典均衡算法消除多径信道码间干扰时,自适应迭代的收敛速度较慢的问题,针对EBPSK系统运用基于小波变换的线性均衡器,将输入信号从时域变换到小波域后进行最小均方(LMS)线性均衡,同时根据不同信噪比仿真比较Haar小波、db6小波、sym6小波等经典小波的线性均衡器均衡效果.仿真结果表明:经过小波变换后输入信号的自相关矩阵的最大特征值与最小特征值之比较大,因此基于小波的线性均衡比经典均衡算法的最小均方误差(MSE)收敛速度明显提高,迭代次数和计算量都有所降低,且均衡器选用不同小波函数在一定程度上会影响误码率,但不明显,其中基于Haar小波比基于sym6小波和db6小波的LMS均衡算法的误码率要低.%The adaptive iterative convergence of classic equalize algorithm to eliminate inter-symbol interference in the extended binary phase shift keying (EBPSK) modulation system is slow. In order to improve it, this paper uses wavelet based linear equalizer for EBPSK system, which transforms the input signal from the time domain into the wavelet domain, then uses least mean square (LMS) linear equalizer. Meanwhile, under various signal-to-noise ratios this paper compares the results of different classical wavelet based linear equalizer, i. e. , the Haar, db6, sym6 wavelet. Simulation results show that after wavelet transforming the ratio of the maximum and minimum eigenvalues of the autocorrelation matrix of the input signal is larger. Thus, the convergence speed of minimum mean square error (MSE) based on wavelet-based linear equalizer is faster than that of the widely used classic equalization algorithm, and the number of iterations and computation cost are reduced. Selecting different wavelet function for equalizer affects the error rate to some extent, but the effect is not obvious, while the error rate based on Haar wavelet LMS equalization algorithm is lower than that of sym6 wavelet and db6 wavelet.
展开▼
