摘要
提出了一种基于软迭代的叠加训练序列信道估计方法.该方法将周期性训练序列与用户信息序列叠加后一起发送,通过软迭代方法,在接收端利用信道译码器输出的软信息来计算信息序列的一阶统计量,并将其反馈给信道估计器,用于消除观测量中来自未知信息的干扰,因此提高了信道的利用率和信道参数的估计精度.仿真结果表明,该方法有效地改善了信道估计性能,降低了接收机的误码率,提高了功率效率.
A soft-iterative channel estimation approach using superimposed training sequence was proposed.A periodic training sequence was added（superimposed） to user′s information sequence at the transmitter.In the channel estimation process the soft-iterative approach was adopted.By utilizing the soft output of channel decoder from receiver to calculate the one-order statistical quantity and return it to channel estimator,the channel estimation accuracy and the utility rate were improved due to eliminating the interference from the unknown data.Simulation results show the benefits of the proposed approach on the channel estimator,bit error rate（BER） performance and power efficiency.
出处
《大连理工大学学报》
EI
CAS
CSCD
北大核心
2011年第6期911-915,共5页
Journal of Dalian University of Technology
关键词
信道估计
叠加训练序列
软迭代
channel estimation
superimposed training sequence
soft-iterative
