Turbo码是一种常用的信道编码方式,正确识别Turbo码首先要正确识别其子递归系统卷积(recursive system convolutional,RSC)码,由于信道噪声与干扰引发误码,这就要求识别算法具有良好的抗误码性能以及识别能力。利用解调软判决序列,通过...Turbo码是一种常用的信道编码方式,正确识别Turbo码首先要正确识别其子递归系统卷积(recursive system convolutional,RSC)码,由于信道噪声与干扰引发误码,这就要求识别算法具有良好的抗误码性能以及识别能力。利用解调软判决序列,通过编码码元约束方程,构建指数形式的代价函数模型,将识别RSC码的生成矩阵问题转化为求解代价函数全域极值的最优化问题,最后在共轭梯度法的基础上,采用新的PRP步长因子来寻找全域极值点。仿真结果表明,所提算法与现有算法相比,收敛速度更快,在低信噪比下也有良好的识别能力。展开更多
The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the code...The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the codeword length and constraint length,the search space expands exponentially,and thus it limits the application of these methods in practice.To overcome the limitation,a novel identification method,which gets rid of exhaustive test,is proposed based on the cuckoo search algorithm by using soft-decision data.Firstly,by using soft-decision data,the probability that a parity check equation holds is derived.Thus,solving the parity check equations is converted to maximize the joint probability that parity check equations hold.Secondly,based on the standard cuckoo search algorithm,the established cost function is optimized.According to the final solution of the optimization problem,the generator matrix of recursive systematic convolutional code is estimated.Compared with the existing methods,our proposed method does not need to search for the generator matrix exhaustively and has high robustness.Additionally,it does not require the prior knowledge of the constraint length and is applicable in any modulation type.展开更多
The concatenated codes are widely used in current communication systems, such as satellite communication systems and WiMAX system. The objective of this study was to present a low complexity iterative soft decoding al...The concatenated codes are widely used in current communication systems, such as satellite communication systems and WiMAX system. The objective of this study was to present a low complexity iterative soft decoding algorithm for concatenated codes. The concatenation was between a Reed-Solomon (RS) code and recursive systematic convolutional (RSC) code. The reduction in computational complexity was achieved by simplifying the Chase-2 decoder for RS codes with limited usage of test patterns. The processing of soft information between inner and outer decoders was also discussed. Simulation results showed that the proposed algorithm could achieve a good trade-off between complexity and performance.展开更多
文摘Turbo码是一种常用的信道编码方式,正确识别Turbo码首先要正确识别其子递归系统卷积(recursive system convolutional,RSC)码,由于信道噪声与干扰引发误码,这就要求识别算法具有良好的抗误码性能以及识别能力。利用解调软判决序列,通过编码码元约束方程,构建指数形式的代价函数模型,将识别RSC码的生成矩阵问题转化为求解代价函数全域极值的最优化问题,最后在共轭梯度法的基础上,采用新的PRP步长因子来寻找全域极值点。仿真结果表明,所提算法与现有算法相比,收敛速度更快,在低信噪比下也有良好的识别能力。
文摘The existing methods for identifying recursive systematic convolutional encoders with high robustness require to test all the candidate generator matrixes in the search space exhaustively.With the increase of the codeword length and constraint length,the search space expands exponentially,and thus it limits the application of these methods in practice.To overcome the limitation,a novel identification method,which gets rid of exhaustive test,is proposed based on the cuckoo search algorithm by using soft-decision data.Firstly,by using soft-decision data,the probability that a parity check equation holds is derived.Thus,solving the parity check equations is converted to maximize the joint probability that parity check equations hold.Secondly,based on the standard cuckoo search algorithm,the established cost function is optimized.According to the final solution of the optimization problem,the generator matrix of recursive systematic convolutional code is estimated.Compared with the existing methods,our proposed method does not need to search for the generator matrix exhaustively and has high robustness.Additionally,it does not require the prior knowledge of the constraint length and is applicable in any modulation type.
基金supported by the National High-Tech Research and Development Program of China (2006AA01Z263)the Research Fund of National Mobile Communications Research Laboratory,Southeast University (2008A10)
文摘The concatenated codes are widely used in current communication systems, such as satellite communication systems and WiMAX system. The objective of this study was to present a low complexity iterative soft decoding algorithm for concatenated codes. The concatenation was between a Reed-Solomon (RS) code and recursive systematic convolutional (RSC) code. The reduction in computational complexity was achieved by simplifying the Chase-2 decoder for RS codes with limited usage of test patterns. The processing of soft information between inner and outer decoders was also discussed. Simulation results showed that the proposed algorithm could achieve a good trade-off between complexity and performance.
