Research on the Handoff for Urban Rail Transit Based on IGM-BP Algorithm

Abstract

Aiming at the problem that the reference signal received power (RSRP) value received by the urban rail transit train during the handoff fluctuates greatly, which causes frequent occurrence of ping-pong handoff, combined with the A3 event in the TD-LTE standard, the improved grey prediction-BP neural network (IGM-BP) algorithm was proposed to improve RSRP fluctuations. The terminal access unit (TAU) will receive the first four sets of RSRP values at time t to establish a grey model GM (1,1) and get a set of predicted values. Take the average of the predicted value as the expected value, and finally the predicted values, modified by the BP neural network algorithm, are used to obtain the expected RSRP value. The simulation results show that the proposed algorithm, compared with the traditional handoff algorithm and the grey prediction algorithm, decreases the RSRP value fluctuation range, reduces the ping-pong handoff rate and meets the requirement that the TD-LTE system handoff success rate reaches 99.5%.