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首页> 外文期刊>Journal of Zhejiang University. Science >RLS channel estimation with adaptive forgetting factor in space-time coded MIMO-OFDM systems
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RLS channel estimation with adaptive forgetting factor in space-time coded MIMO-OFDM systems

机译：空时编码MIMO-OFDM系统中具有自适应遗忘因子的RLS信道估计

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摘要

Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.
机译：考虑到信道估计在相干检测中起着至关重要的作用，本文提出了一种在无线空时编码多输入和多输出正交频分复用中采用具有自适应遗忘因子的递归最小二乘（RLS）信道估计的方法（ MIMO-OFDM）系统。由于存在三种不同的遗忘因子场景，包括自适应，两步和常规的遗忘因子场景，因此本文介绍了RLS信道估计的原理，并分析了不同遗忘因子场景对RLS信道估计性能的影响。仿真结果表明，在多输入上，具有自适应遗忘因子（RLS-A）的RLS算法在两步遗忘因子（RLS-T）或常规遗忘因子（RLS-C）方面均优于传统算法多输出（MIMO）信道，即，宽广的固定不相关散射（WSSUS）和频率选择性慢衰落信道。因此，我们可以通过自适应地调整遗忘因子来采用RLS-A方法，以在空时编码MIMO-OFDM系统中成功地跟踪和估计信道状态参数。

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