基于常数模算法的空间分集盲均衡技术

Research on Spatial Diversity Blind Equalization Based on Constant Modulus Algorithm

针对传统的自适应均衡技术需要重复发送训练序列,占用大量带宽,及Bussgang类盲均衡算法在收敛速度、稳态误差以及克服相位旋转等方面性能较差的缺陷,研究了Bussgang类盲均衡算法与不同的分集合并技术相结合的方法,提出了基于常数模算法的空间分集盲均衡技术,以适应远距离通信,提高接收信噪比和更有效地克服信道衰落。计算机仿真实验结果证明该技术比传统的判决反馈均衡器具有更快的收敛速度和更低的稳态误差。

Unlike conventional adaptive equalization,Bussgang blind equalization operates without training sequence,which can save bandwidth and achieve higher date rate with strong robustness and be easily implemented,is widely used.The problems,however,such as slower convergence rate,larger residual error and phase-blind nature may not be sufficient for system to obtain adequate performance.Accordingly,we study the method of combining Bussgang blind equalization with different diversity combining technique.A spatial diversity method based on constant modulus algorithm is proposed.It can be suitable to long-range communication and is an effective way to improve SNR and suppress distortion.Compared with the decision feedback equalizer the proposed method can obtain faster convergence rate and lower steady state mean square error.