Research On Distributed Cooperative Localization For Mobile Communication Newtork

In recent years,the 5th-Generation Mobile Communication Technology(5G)and Internet of Things(IoT)technology have been rapid development,to provide users with real-time,fast,high-precision location services and reliable,continuous navigation services is the current and future communication network key and essential basic capabilities.Global Navigation Satellite System(GNSS)has a very good positioning performance in outdoor and open scenes,which can meet the needs of most users.However,it is still an urgent problem to provide real-time,seamless and high-precision location services in indoor areas with numerous and complex shelter objects,large supermarket areas with abundant hot spots and dense personnel,and urban canyon areas with numerous high-rise buildings.Ultra-Dense Network(UDN)and device-to-device(D2D)technology are the key candidates for 5G mobile communication systems.It can reduce the non-line of Sight(NLOS)transmission of wireless signals and realize the two-way communication and information sharing between nodes,providing technical support for the implementation of collaborative positioning scheme.This paper studies the problem of distributed co-location for mobile communication network,and the specific work is as follows:Firstly,the measurement model parameters of Received Signal Strength Indication(RSSI)change with dynamic environment,which leads to large ranging error,and the propagation characteristics of wireless signals are studied.A RSSI-Based Environment Adaptive Ranging Model(RARM)is proposed.RARM uses the location redundancy information of anchor nodes or target nodes with known locations to update the RSSI ranging model parameters in real time,dynamically and periodically,and broadcast them to the collaborative network to assist other nodes in ranging.The target node is located by using the RSSI value processed by Gaussian mixture filter and the ranging model parameters with periodic changes.The measured results show that the positioning accuracy of the proposed WLS location algorithm using the REARM model is 23.73%higher than that using the fixed model parameters.In the time-varying environment,the REARM can still maintain good ranging performance,which enhances the robustness of the ranging model to the time-varying environment.Then,based on the RSSI ranging model in the adaptive environment proposed in the previous paper,the objective function structure of co-location of D2D communication network is complex and non-convex,and the traditional co-location algorithm is difficult to obtain the optimal location solution.A distributed co-location algorithm based on Classification Particle Swarm Optimization(CPSO)is proposed.CPSO algorithm can divide particles into short range particles,medium range particles and long range particles according to the generation value,and set different inertia weights and learning factors for different kinds of particles,so as to enhance the optimization ability of the algorithm and effectively improve the positioning accuracy.In order to reduce the number of links in D2D communication networks,this paper proposes a node sending optimization mechanism based on Cramero Lower Bound(CRLB),which selects nodes at the sender and prevents the location information propagation of pseudo-anchor nodes whose location estimation is unreliable.The simulation results show that the proposed distributed co-location algorithm based on CPSO improves the location accuracy by 25.3%compared with the classical PSO algorithm in NLOS environment,and reduces the average number of links in D2D communication network by 11.17%without losing the co-location accuracy,which effectively reduces the network traffic.