Font Size: a A A

The Research Of LTE-R Handoff Algorithm Based On Fuzzy Prediction

Posted on:2021-02-01Degree:MasterType:Thesis
Country:ChinaCandidate:Q WenFull Text:PDF
GTID:2392330605961144Subject:Electronic and communication engineering
Abstract/Summary:PDF Full Text Request
In recent years,the rapid development of China's high-speed railways,with its high punctuality rate,high transportation capacity,comfortable and safe ride,etc.,high-speed railways have become more and more widely used in China's transportation,while driving rapid economic development.With the speed-up of high-speed rail and the increase in passenger network demand,the current railway dedicated mobile communication system GSM-R has been unable to meet the service needs.LTE-R has become an international railway alliance with its high channel capacity,high frequency bandwidth and high rate transmission UIC)The next-generation mobile communication system approved,LTE-R,as a new-generation railway communication system,not only improves communication performance,but also satisfies passengers demand for wireless communication.Handover as the core technology of high-speed railway communication system,Excellent handover algorithm is the basis of keeping communication continuous without interruption,it makes handoff algorithm become the hot spot of current research.From the perspective of LTE-R system switching technology,this paper analyzes how to improve the stability and reliability of communication system,and further improve the performance of handoff.Firstly,through the introduction of the background and significance of handoff,LTE-R communication system is introduced,network architecture,network element function and interface protocol of LTE-R system are introduced in detail.It shows that LTE-R system has unique advantages in high-speed railway mobile communication.For the high-speed railway LTE-R handover process,the handover algorithm based on A3 event judgment is prone to frequent ping-pong handover and low handover success rate.Improved fuzzy prediction optimization switching algorithm.The algorithm performs the measurement parameter reference signal received power(RSRP)during the handover process,and optimizes the collected measurement parameter RSRP value through the improved gray GM(1,1)algorithm.After the processing,the measurement parameter value goes through 3 cycles Predict and weight the average,and send it to the decision formula to make a decision.The algorithm is simulated in MATLAB.The results show that the algorithm reduces the "ping-pong handover" caused by signal fluctuations to a certain extent,and improves the success rate of handover.Secondly,based on the unreliability of the handover based on the signal strength based on the traditional A3 handover algorithm,a handover invitation scheme based on handover invitation in high-speed railway communication system is proposed.At the time of zone handover,the base station sends a handover invitation to the mobile terminal,and the train performs handover,which reduces the handover decision process and simplifies handover signaling.Compared with the traditional handover scheme,it reduces the probability of handover interruption,improves the probability of handover success,and better adapts to high-speed railway scenarios.Finally,in order to further improve the performance of handover,a cooperative handover algorithm is proposed.The handover invitation algorithm and the improved GM(1,1)algorithm are fused and reconstructed,and the A3 assisted decision process is added to ensure the reliability of the handover.And improve the reusability of the system.Through simulation comparison,the results show that,compared with the traditional handover algorithm and the improved GM(1,1)handover algorithm,the proposed cooperative handover algorithm has a significant decrease in the probability of outage and handover failure,and the handover success rate is obtained.This improves the performance of handover.
Keywords/Search Tags:High-speed railway, LTE-R, handover, grey prediction, measurement parameters
PDF Full Text Request
Related items