突发通信中基于叠加训练的信道估计方案

针对无线突发通信中频带利用率低、信道参数获取困难等问题,提出了一种应用于突发通信的叠加训练信道估计与检测方案。该方案将信息和训练叠加发送,通过预失真发送信息符号使得训练与信息在频域正交,收端采用一阶统计信道估计和最大似然符号检测,并设计了抗直流干扰的信道估计方案。仿真表明,新方案在消除训练序列的频带开销的情况下获得了较好的信道估计和符号检测性能,与采用时分复用训练的方案相比,其有效吞吐率更优。

Channel estimation using superimposed training in burst communication

In wireless burst communication, the bandwidth efficiency is low and the channel parameters are difficult to acquire. To solve these problems, a channel estimation and detection scheme for burst communication is proposed using superimposed training (ST). In this scheme, the information and training are added together at the transmitter, where the training symbols are predistored for training-information orthogonalization in frequency domain. At the receiver, a first-order statistic-based channel estimation algorithm is adopted in conjunction with a maximum likelihood sequence detection method. The channel estimation algorithm is also immune to dc-offset interference. Simulation results show that the new scheme has fairly well channel estimation and symbol detection performance without any training bandwidth overhead, leading to a better effective throughput performance when compared to the schemes using time division multiplexed (TDM) training.