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A comparison of several strategies for iteratively decoding serially concatenated convolutional codes in multipath Rayleigh fading environment

机译:在多径瑞利衰落环境中迭代解码级联卷积码的几种策略的比较

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We investigate two iterative methods for decoding serially concatenated convolutional codes (SCCC) on multipath Rayleigh fading channels. One method employs optimal maximum a posterior (MAP) decoders or sub-optimum versions. The second slightly differs and is based on a soft-in soft-out (SISO) parallel decision-feedback decoder (PDFD), used for iteratively performing joint equalization and inner decoding together with outer decoding. Simulation results show that the first iterative process is only 0.7 dB better than the second one, which is however far less complex.
机译:我们研究了两种在多径瑞利衰落信道上解码串行级联卷积码(SCCC)的迭代方法。一种方法采用最佳的最大后验(MAP)解码器或次最佳版本。第二个略有不同,它基于软输入软输出(SISO)并行决策反馈解码器(PDFD),用于迭代执行联合均衡和内部解码以及外部解码。仿真结果表明,第一个迭代过程仅比第二个迭代过程好0.7 dB,但是复杂程度要低得多。

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