Analysis And Optimization Strategy On AoI In Multi-Tier Cellular-based IoT Networks

With the vigorous development of the Internet of things（Io T）,there are more and more communication applications with the demand of information timeliness.Age of information（AoI）is proposed as a new performance index,because the traditional performance indexes can not accurately describe the timeliness of information,such as delay,jitter and throughput.In recent years,the research on the performance analysis and optimization technology of AoI in Io T network has attracted much attention in industry and academia.The research on AoI mostly stays in the network of single link,while the research on AoI in large Io T network is very few,such as multi-tier heterogeneous networks.Multi-tier heterogeneous cellular networks can provide ubiquitous and personalized connection for massive Io T devices,which has become the mainstream network architecture of Io T communication network.Analyzing AoI of status update under the network architecture will help to understand the key network elements that restrict the timeliness of information.Based on this,designing the optimization strategy of AoI can greatly improve the timeliness of information and better meet the communication requirements of high timeliness services.This dissertation aims to analyze AoI in multi-tier cellular-based Io T communication networks,and further combine the device association and power control strategy to optimize AoI performance.The main work of this dissertation includes:（1）For the uplink transmission network of Io T based on multi-tier cellular network architecture,considering spatial random distribution characteristics of Io T devices and dynamic arrival characteristics of services,the AoI of state updates of typical Io T devices is analyzed by using the stochastic geometry theory,and the conditional successful transmission probability of state update and the scheduling probability of Io T devices are derived,Finally,the tractable expressions of average AoI and peak AoI（PAoI）of status update of the typical Io T device are obtained.（2）For the requirement of information timeliness in Io T,an AoI optimization method combining Io T device association and power control strategy is proposed to improve the AoI performance of state update.On the one hand,the device association strategy based on weighted path loss is adopted to optimize the scheduling probability of the device by adjusting the load of Io T device associated with the aggregation BSs of different tiers;On the other hand,the fraction power control strategy is adopted to adjust the transmission power of Io T device,and the successful transmission probability of Io T device is improved by reducing the network cumulative interference.The AoI and PAoI are finally optimized by jointly optimizing the association weight of Io T device to different tiers of aggregation BSs and the power control factors of Io T device.（3）Build a simulation platform,select reasonable network parameters,conduct simulation and theoretical comparative analysis,and verify the correctness of theoretical analysis and the effectiveness of the proposed optimization strategy.Simulation results show that the proposed theoretical analysis framework can effectively describe the AoI and PAoI performance of state update in the scenario of random distribution of Io T devices,and can be used to solve the optimal device association strategy and the power control factor.In particular,it is found that when the association weights of aggregation BSs in different tiers are the same,that is,when the nearest association strategy is adopted,the minimum AoI and PAoI of state update can be obtained.