An Algorithm of Long Term Evolution-5G Data Transmission Based on Gray Fuzzy Bayesian Network to Monitor Health Parameters

摘要

Aiming at the problems of poor data transmission accuracy and small transmission bandwidth in mobile communication systems, this paper proposes an Long Term Evolution-5G (LTE-5G) data transmission algorithm based on gray theory. On the basis of LTE-5G data mapping, the constellation graph of LTE-5G data transmission was designed so as to complete the one-time formation of data transmission and reduce the influence of Rayleigh noise on the normal mapping process of data. Aiming at the channel error caused by the crossing phenomenon between projections in the transmission constellation and the regional overlapping phenomenon, the gray fuzzy Bayesian network was used to process the gray fuzzy domain and probability data. The results of fuzzy data evaluation were transformed into knowledge in the probability domain by the theory of probability conversion. In the probability knowledge domain, the Bayesian network reasoning algorithm was used to extract the fuzzy data. And then, a grouped fault-tolerant model of transmission constellation was constructed. The protocol fields were repaired by the maximum posterior estimation of the receiver. Finally, the forward error control without the coding sender was completed. Thus, the accuracy of LTE-5G data transmission was improved. Experimental results show that the proposed algorithm has higher data transmission accuracy and bandwidth.