Multi-Objective Optimization Design For Architecture Of Regional Coverage Space Information Networks

With the "space economy" and "Internet economy" has gradually become a new growth point of economic development,the world more and more attention to the development of space information network(Space Information Networks,SIN).Combined with China's national conditions,the construction and deployment of regional coverage for the spatial information network is the only way to achieve network power,but also the ultimate realization of the global coverage of information networks and the premise of the premise.The optimization of the spatial information network structure is the top design of SIN.According to the SIN hierarchical structure,the optimization process can be divided into the optimization of the high altitude platform(HAP)network and the space constellation satellite constellation network.In view of the complexity of the network structure and the diversity of the optimization direction,the structure optimization design is modeled as a multi-objective and multi-constrained optimization problem for the network service to match the demand distribution of the target area as much as possible.Network and space segment satellite constellation optimization design research.The main work of this paper is as follows:Considering the complex SIN structure optimization is a complex combinatorial optimization problem,the second chapter introduces the multi-objective evolutionary algorithm,and introduces the non-dominated sorting genetic algorithm(NSGA2).Then,aiming at the shortcomings of NSGA2 in solving practical problems,this paper proposes an improved NSGA2 with dynamic inverse learning mechanism and differential local variation operator.By using the standard test function and evaluation index,it is observed that compared with the original algorithm,The convergence and distribution of the solution are better.Aiming at constructing SIN by multi-HAP in a wide area,a multi-objective optimization design method for wide area coverage HAP communication network is proposed.Considering that HAP can only service the coverage area users and the signal interference in the coverage area,a wide area coverage HAP communication network model is established.Based on this,in order to consider the factors such as resource allocation,service reachability and load cost,combined with the demand distribution in the target area,the equivalent isotropic radiated power and the deployment position of HAP are used as design variables.Finally,the simulation is carried out with the target area in the South China Sea,and the improved NSGA2 model is used to solve the model.The proposed method can effectively solve the wide-area coverage HAP optimal deployment problem.Aiming at constructing SIN by multi-HAP over the city,the fourth chapter proposes a multi-objective optimization method for HAP-VMIMO communication network.Considering that HAP can provide services for the same users through signal merging at the same time,HAP-VMIMO communication is formed by multiple HAPs constituting virtual multiple-input multiple-output(VMIMO)Network model,and proposes a multi-objective optimization deployment method based on the network capacity resource matching user demand distribution to improve the network capacity of the lifting system.Finally,the Yangtze River Delta urban agglomeration is simulated,and the effectiveness of the optimized deployment method is verified.Aiming at constructing SIN by satellite constellation,a kind of multi-objective optimization design method of regional coverage strong invulnerability satellite constellation is proposed.First,we analyze the invulnerability index applicable to the unstructured static network: natural connectivity.Based on this,the invulnerability measure of single-layer satellite network and HAP-MEO-GEO hybrid satellite network is proposed,and the Walker and Flower constellations are put forward.Then,the constellation optimization model with invulnerability measure and coverage as the optimization target is established,and the model of multi-objective evolutionary algorithm is described in detail.Finally,the Pareto solution of the Walker and Flower configurations with 12 satellites in the single-layer satellite network is solved and obtained with the land area of our country,which verified the feasibility of covering the area with strong invulnerability satellite constellation.