Iterative channel estimation and coded symbol detection for dispersive channels

B. Unal, A. Berthet, R. Visoz
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引用次数: 4

Abstract

We propose two pilot symbol aided iterative algorithms for channel re-estimation to be used in iterative detection and decoding (turbo-detection) of signals transmitted over frequency selective channels. The first algorithm is based on the expectation-maximization (EM) algorithm that makes use of a signal decomposition to compute separate dosed form recursion expressions for the channel coefficient re-estimates. The a posterior conditional channel state probabilities required by the EM-based turbo-estimation can be easily provided by the forward-backward trellis search performed by the soft-in soft-out (SISO) ISI decoding task. The second algorithm is based on the well-known bootstrap algorithm where soft information from the outer decoder is used to make hard decisions on transmitted coded data, and the detected coded data are used in the channel turbo-estimation process via the conventional linear pseudo-inverse method. Both of the proposed channel turbo-estimation algorithms are naturally embedded in the framework of the turbo-detector, bringing almost no overhead to the receiver complexity.
色散信道的迭代信道估计与编码符号检测
我们提出了两种导频符号辅助的信道重估计迭代算法,用于频率选择信道上传输的信号的迭代检测和解码(涡轮检测)。第一种算法基于期望最大化(EM)算法,该算法利用信号分解来计算信道系数重新估计的单独剂量形式递归表达式。后验条件信道状态概率可以通过软入软出(SISO) ISI译码任务的前向向后网格搜索得到。第二种算法基于众所周知的自举算法,利用外部解码器的软信息对传输的编码数据进行硬决策,并通过传统的线性伪逆方法将检测到的编码数据用于信道涡轮估计过程。所提出的两种信道turbo估计算法都自然地嵌入在turbo检测器的框架中,几乎没有增加接收机复杂度的开销。
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