一种基于叠加训练序列的半盲信道估计方法

A method of semi-blind channel estimation based on superimposed training sequence

为了减少信道估计的带宽损失和提高估计精度,提出叠加训练序列半盲信道估计方法.将设计的优化周期训练序列小功率叠加在信息数据上,采用一阶统计量,用线性最小均方误差均衡的硬判决来量化信息序列进行迭代估算.叠加序列和信息序列共同被利用,改善了估计性能.叠加不同的优化序列进行仿真.结果表明,这种半盲估计方法在算法上简化了矩阵求逆,计算量较小,估计精度较高.

In order to reduce the bandwidth loss of channel estimation and improve the estimation accuracy,a method of semi-blind channel estimation based on superimposed training sequence is proposed.The low power of the designed training sequence of optimal period is superimposed on the information data,and the information sequence is quantified by using the first-order statistics and the hard judgment of linear least mean square error equilibrium for iterative estimation.The hard decision of linear MMSE equalization be adopted to quantify the information sequence for iterative estimation.The superimposed training sequence and the information sequence are used together to improve the estimation performance.Different optimal sequences are superimposed for simulation.The results show that this semi-blind estimation method can simplify the inverse matrix algorithm,and the computation is small and the estimation accuracy is high.