MIMO-OFDM系统中一种改进的递归最小二乘(RLS)信道估计方法可以在不需要任何信道统计信息的前提下,利用前导训练序列和自适应遗忘因子对信道状态参数进行估计。仿真结果表明基于自适应遗忘因子改进的RLS信道估计方法(RLS-A),在估计精度和鲁棒性上的性能均优于基于常规遗忘因子的RLS信道估计方法(RLS-C)和两步遗忘因子的RLS信道估计方法(RLS—T).因此,改进的RLS-A隆遵估计方法能很好地满足MIMO-OFDM系统中接收机的要求.
The modified recursion lest squares (RLS) channel estimation method exploits preamble training sequences and adaptive forgetting factor to estimate channel state parameters without any prior statistics knowledge of channel in multiple input multiple outputorthogonal frequency division multiplexing (MIMO-OFDM) systems. Simulation results confirm that the RLS channel estimation method with adaptive forgetting factor (RLS-A) outperforms that with conventional forgetting factor (RLS-C) or with two-step forgetting factor (RLS-T) in both estimation accuracy and robustness. Therefore, the modified RLS channel estimation method can satisfy the requirement of the receiver for MIMO-OFDM systems.