Research And Implementation Of Key Technologies For Physical Uplink Shared Channel Based On 5G NR

The commercialization of fifth-generation mobile communication(5G)systems has had a multifaceted impact on the development of the era,and the application of three major scenarios provides new solutions to the challenges faced by various industries.At the same time,with the continuous development of 5G networks,the development of radio access network(RAN)towards virtualization,cloudization and openness.This puts forward new requirements for RAN’s software system with low coupling,high real-time and good portability.Based on these two backgrounds,this paper investigates the channel estimation technology and low-density parity check(LDPC)code technology involved in the physical uplink shared channel(PUSCH)of the 5G New Radio(NR),and designs and implements a multi-core server-based PUSCH software system based on the implementation of these two technologies.Firstly,the paper builds a PUSCH link simulation system after studying the basic theory of5 G physical layer.In order to solve the problems caused by multipath fading and Doppler shift,this paper uses the discrete cosine transform(DCT)based algorithm to perform channel estimation of PUSCH link.The algorithm converts the obtained channel estimation to time domain by inverse discrete cosine transform(IDCT),sets the window and energy threshold for noise energy rejection,and finally obtains the channel estimation parameters by DCT.This algorithm has better performance compared with the least squares(LS)algorithm,with about 0.8 d B improvement at the same bit error rate(BER);it requires less channel information compared with the minimum mean square error(MMSE)algorithm,and only requires two time-frequency conversions and sampling point screening based on the LS algorithm,without complex matrix inversion operations.Secondly,in order to handle channel errors,this paper selects the density evolution theorybased least-sum algorithm(DEOMS)as the LDPC decoding part of the link on the basis of completing the simulation of the performance and iteration number of several soft-judgment decoding algorithms.The performance of this algorithm has about 0.08 d B improvement compared with the least-sum algorithm(OMS),and the execution efficiency of the algorithm has lower time complexity compared with the logarithmic domain confidence propagation algorithm(LLR-BP),which is suitable for PUSCH links.Finally,the paper designs and implements a software processing system based on a multicore server.The system makes full use of the resources of the multi-core server to improve the parallelization of the link and speed up the PUSCH link task processing.The actual system is tested and the results are compared with matlab theoretical data to verify its correctness.And the average execution time of one time slot is 0.3528 ms,which is less than one time slot cycle can meet the design requirements.