Low-complexity Joint Channel Estimation and Decoding for LDPC Codes Via Sliding-Window Belief-Propagation over Non-stationary Channels
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摘要: 随着移动通信应用场景的持续增多，非平稳信道成为越来越常见的传输环境，而非平稳信道下的可靠传输依赖于准确的信道估计。基于信源编码中用于信源参数估计和信源相关性估计的滑窗置信传播(SWBP)算法，该文提出一种非平稳信道下LDPC码的联合信道估计与译码(JCED)算法；同时，分别基于交叉熵和离散傅里叶变换提出两种在每轮JCED迭代中自适应设置滑窗长度的快速算法。仿真结果表明，在无导频辅助的前提下，所提算法具有接近理想信道估计下置信传播译码的性能以及高效率、低复杂度、强鲁棒性和不导致错误平层等优点。Abstract: With the continuous increase of possible usage scenarios of mobile networks, non-stationary channels become more and more common transmission environments, and reliable transmission over non-stationary channels relies on accurate channel estimation. Based on the Sliding-Window Belief-Propagation (SWBP) algorithm used to cope with source parameter estimation and source correlation estimation, a Joint Channel Estimation and Decoding (JCED) algorithm for LDPC codes over non-stationary channels is proposed. Two fast algorithms to set adaptively the window size in each JCED iteration are also proposed based on cross entropy and Discrete Fourier Transform (DFT), respectively. Simulation results reveal that, without the aid of pilots, the performance of the proposed algorithm approaches that of Belief-Propagation (BP) decoding under ideal channel estimation, and has the advantages of high efficiency, low complexity, strong robustness and not incurring error-floor.
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