基于弱能量并行训练序列的OFDM信道估计

Channel Estimation for OFDM Using Parallel Training Sequences with Low Power

研究获得OFDM信道的信道状态信息,提高信道的传输性能,针对快速信道传输中提高传输率,提出了一种基于弱能量并行训练序列的信道估计算法,算法中训练序列直接叠加到发送的信息数据上,在接收端利用并行训练序列来进行信道估计。仿真结果显示,所提算法的性能与基于导频的LS、MMSE算法性能相当,且在低信噪比时稍优于LS算法。采用m序列、ZCZ序列和最优周期训练序列时都能达到很好的BER信道估计性能,可选择的训练序列的范围更广,并进行仿真。结果表明,算法提高了信道传输性能,计算复杂度低,并具有很好的灵活性,对无线通信系统有效,为系统设计提供了依据。

In order to obtain the channel state information of OFDM channel and improve the transmission performance of the channel,this paper investigates channel estimation using parallel training sequences with low power.The training sequences are directly added to information data in the transmitter in the algorithm,and the algorithm uses the parallel training sequences for the channel estimation in the receiver.Computer simulation results show that the proposed method performance is close to the performance of LS and LMMSE methods based on pilot signals,and is slightly better than LS method at low SNR.The proposed method can all achieve good BER performance of channel estimation by using m sequences,ZCZ sequences and optimal periodic training sequences,and has a wider range of available training sequences.The transmission performance of the channel is improved,and the proposed algorithm has the lower computational complexity and good flexibility.Thus,it is very effective for the wireless communication system.