| The advent of the 5th Generation Mobile Communication Technology(5G)has put forward higher quality requirements for information transmission rate,communication delay and system throughput.As one of the important technologies,Adaptive Modulation and Coding(AMC)technology can select a Modulation and Coding Scheme(MCS)that adapts to the current channel state as the mobile communication environment changes.Under the premise of transmission quality,the information transmission rate is increased,which effectively improves the throughput and spectrum efficiency of the system.Channel coding technology and Channel Quality Indicator(CQI)are the keys to ensure reliable and effective transmission of AMC systems.Therefore,based on the data transmission protocol of the 5G communication system,this paper focuses on the decoding algorithm of the Low-Density Parity Check(LDPC)code and the CQI measurement algorithm in the AMC technology.Aiming at the problem of the CQI measurement algorithm in the adaptive coding and modulation technology,the CQI measurement scheme in 5G is firstly analyzed,and the Exponential Effective SINR Mapping(EESM)algorithm is mainly studied.The EESM algorithm is derived from the Chernoff boundary of the symbol error rate,using an information measure function and a scale factor to equivalence the SNR on the subcarriers.Then,the effective signal-to-noise ratio under the corresponding additive white Gaussian noise(AWGN)channel is obtained.Since the link simulation process is carried out with a specific step size,it is inevitable to fall between the SNR simulation points in the process of finding the equivalent SNR corresponding to the block error rate.In this paper,the AWGN performance curve is fitted by fitting the model function,which reduces the interpolation error and improves the simulation efficiency.On this basis,an improved SNR mapping algorithm is proposed to better complete the effective SNR mapping from the actual channel to the AWGN channel,and improve the accuracy of the mapping.The simulation results show that,compared with the traditional EESM algorithm,the improved signal-to-noise ratio mapping algorithm has higher prediction accuracy and smaller root mean square error,which has certain practicability.With its unique advantages,LDPC codes have been identified as the channel coding scheme in the 5G enhanced Mobile Broadband(e MBB)scenario.This paper first studies the Belief Propagation(BP)algorithm of LDPC codes and introduces the process of simplifying the BP algorithm by algorithms such as Min-Sum(MS)and Normalized Min-Sum(NMS),the error caused by simplifying the approximation is analyzed.On this basis,an improved decoding algorithm based on NMS is proposed.By calculating the optimal correction factor in the iterative process,it can better correct the error generated by the approximate calculation and improve the decoding performance.The parameters are then optimized to achieve a compromise between complexity and decoding performance.The simulation shows that the proposed algorithm has better decoding performance than the traditional NMS algorithm and is generally applicable to LDPC codes corresponding to different base matrices and boosting factors in 5G and has a performance improvement of about 0.12 d B in terms of long codes. |
