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Performance Analysis of the Iterative Turbo Decoding Stopping Criteria in AWGN Channel

机译:AWGN信道中Turbo迭代译码停止准则的性能分析

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The variances in the channel estimates errors is the factor that affected the channel reliability factor in iterative turbo decoding, due to the flawed in the estimates of the signal-to-noise ratio (SNR). However, most of the stopping criteria approaches in turbo decoding assumed the channel reliability at the receiver is known with respect to the threshold. Under additive white Gaussian noise (AWGN) channel, three stopping criteria for iterative decoding are analyzed in this paper. The Cross-entropy (CE), Hard Decision Aided (HDA) and Sign-Change Ratio (SCR) are utilized for the simulation process by comparing the reliability channel stopping criteria. It is further enhanced by expanding puncturing method the rate of the system for AIN. At high SNR, the scaled received data results in the stopping criteria to stop iteration sooner while keeping up the BER performance, however more regrettable at certain frame size. Consequently, the different frame size does not influence the BER performance either in unscaled or scale condition.
机译:由于信噪比(SNR)估计中的缺陷,信道估计误差中的方差是影响迭代turbo解码中的信道可靠性因子的因素。但是,在turbo解码中,大多数停止标准方法都假设相对于阈值已知接收器的信道可靠性。本文在加性高斯白噪声(AWGN)信道下,分析了三种迭代解码停止准则。通过比较可靠性信道停止标准,将交叉熵(CE),硬决策辅助(HDA)和符号变化率(SCR)用于仿真过程。通过扩展打孔方法可以进一步提高AIN系统的速率。在高SNR时,缩放后的接收数据会导致停止准则,以便在保持BER性能的同时更快地停止迭代,但是在某些帧大小下更令人遗憾。因此,不同的帧大小在未缩放或缩放条件下均不会影响BER性能。

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