瑞利衰落电离层信道的自适应盲均衡

研究通过具有加性高斯白噪声的瑞利慢衰落电离层信道的恒模盲均衡技术。著名的恒模算法(CMA)是一种重要的盲信道均衡方法。但是，普通恒模算法存在收敛速度慢和相位旋转等不足。采用一种修正恒模算法(MCMA)，该算法使修正的误差函数最小并且自适应学习率由接收序列即时调整。两种算法用8—PSK信号进行了盲均衡比较，模拟结果显示修正恒模算法比普通恒模算法的收敛速度快，符号间干扰(ISI)小，另外该算法均衡器输出具有既无相位旋转也无延迟等优点。

Adaptive blind equalization for Rayleigh fading ionospheric channels

The constant modulus blind equalization technique is investigated over a slow Rayleigh fading ionospheric channels with additive white Gaussian noise. The well-known constant modulus algorithm (CMA) is a very important approach for blind channel equalization. However, the standard constant modulus algorithm has some disadvantages such as the slow speed of convergence and phase rotation. In the paper, a modified constant modulus algorithm (MCMA) is proposed. The proposed algorithm minimizes a modified error function and the learning-rate is multiplied by received sequences. Through a performance comparison for 8-PSK signal constellations,the simulation results demonstrate that the MCMA leads to faster convergence and smaller intersymbol interference (ISI) in steady-state than those obtained using the CMA. In addition, the equalizer output has neither the phase rotation nor the delay.