Symbol Flipping Based Non-binary LDPC Decoding Algorithms And Their Energy Consumption

Low-density-parity-check code(LDPC),as an excellent channel coding,plays an important role in modern communication technology and has been selected as the data channel coding in the 5G communication.Compared with their binary couterparts,Non-Binary LDPC codes usually have better performances,especially for the short code length and moderate to high code rate.The research of Non-Binary LDPC decoding algorithm is mainly to improve the performance of the algorithm,reduce the decoding complexity,and also take into account the convenience of hardware implementation.This thesis mainly studies Non-Binary LDPC decoding algorithms based on symbol flipping,and gives a comparison scheme for complexity based on energy consumption complexity.The main research work and innovations are summarized as follows:1.An improved wtd-AlgB decoding algorithm is proposed:We present a modified wtd-AlgB algorithm with a new weighting factor calculation method.The weighted factor is determined by the number of occurrences of external information and the Hamming distance coefficient between hard decision symbols and the external information,which can improve the decoding performance;2.Truncation-Symbol Flipping Decoding algorithm based on Prediction(T-SFDP)is presented based on D-SFDP algorithm.According to the plurality rule,the presented algorithm computes the flipping function with only those variable nodes satisfying a well-designed relationship between the extrinsic information and a designated threshold.Furthermore,only nT(nT<(q-1)field symbols are involved to compute the prediction value.In contrast to the original algorithm,the presented algorithm can efficiently reduce the complexity and energy consumption,with a neglectable performance degradation.3.Aiming at eliminating the oscillation phenomenon of the D-SFDP algorithm,this thesis introduces a set N to save the subscript information of the flipping variable node,The oscillation state can be observed by the order change in the iterative process.When the number of iterations does not increase,the variable node in N can be selected to perform the flipping operation.For done so,the algorithm can jump out of the oscillation state,which can improve the performance of the algorithm and increase the convergence rate.4.Simulation platform is designed to verify the performance of different decoding algorithms Furthermore,an energy-based measurement criterion is presented to analyze the decoding complexity,which can make a more intuitive and convenient comparison for different algorithms in term of energy consumption.