Research On Tail Energy Consumption Optimization Of Intelligent Terminal In Mobile Network

Nowdays,mobile network has become one of the main ways for intelligent terminal to obtain information resources,and the tail energy consumption generated in the process of data transmission is the key factor leading to poor energy efficiency of intelligent terminal.Therefore,it is significant to reduce the tail energy consumption of intelligent terminal reasonably and effectively.This paper mainly focuses on how to reduce the tail energy consumption of intelligent terminal in mobile network environment,prensents two kinds of optimization methods and obtaines the better energy consumption optimization effect.The main contents of this paper are as follows:1.The RRC state machine model and the generation mechanism of the tail energy consumption in the mobile network are analyzed in detail,and the design flaws of RRC protocol and discontinuous acceptance mechanism(DRX)are pointed out,laying the theoretical foundation for the follow-up study of tail energy consumption optimization.2.Based on the time correlation of 3G data flow,a mobile network tail energy consumption optimization method(BOA)based on time series is proposed to solve the problem of tail energy consumption caused by fixed tail time of RRC protocol.This mechanism predicts the future TAB value by establishing an autoregressive moving average model(ARMA Model)for the observed block time interval sequence(TAB),and dynamically adjusts the tail time according to the predicted value to realize the tail energy consumption optimization of the intelligent terminal in 3G network.3.Aiming at the problem that the single cycle configuration of discontinuous reception mechanism(DRX)in 4G is difficult to adapt to the multi-service concurrent problem,an adaptive DRX optimization mechanism(AM-DRX)based on Markov chain is proposed.This mechanism first establishes the Markov chain model for different data business states to predict the future data business status,and then synthetically adjusts the DRX cycle with the predicted value and the channel monitoring state to realize the tail energy consumption optimization of the intelligent terminal in 4G.4.The simulation experiment is designed to verify the effectiveness of the two methods of tail energy optimization.The experimental results show that the energy efficiency of BOA is improved by 42.25%compared with Fixed-Tail algorithm,and AM-DRX can effectively reduce the terminal energy consumption,and meanwhile the adaptived DRX parameter configuration for data services is realized.