Research On The Optimal Deployment Method Of Communication Stations In Complex Mountain Environment

China is rich in mountainous resources,and it is very necessary to carry out military combat communication,civilian emergency communication and geological disaster monitoring in such an environment.Wireless communication has become the main means of communication in such environments by virtue of its advantages of flexible networking,strong scalability and high timeliness.However,there is a lack of systematic scientific research on the characteristics of such channels,which makes it difficult to establish effective and reliable connections quickly in practical application scenarios and restricts the development of wireless communication in mountainous environments.In view of the complexity of the mountain environment,the type of vegetation,the undulation of the terrain,and the location of the communication station will all have a certain impact on the propagation of radio waves,among which,how to choose the appropriate location of the communication station in the complex mountain environment is a difficult problem in mountain communication.Therefore,this paper carries out the research on the method of communication station deployment in complex mountain environment,aiming to select the suitable communication station placement scheme and achieve the communication objectives such as the minimum number of stations set,the maximum coverage area and the minimum interference between communication stations.The research contents of this paper include:The first part is to address the problem of lack of empirical data on wireless transmission performance in mountainous areas.In this paper,the mountainous environment is divided into three types of typical mountainous environments: mid-latitude high-altitude large undulating non-vegetated mountainous areas,mid-latitude mid-altitude medium undulating broadleaf forest mountainous areas and mid-latitude low-altitude medium undulating shrub mountainous areas,and then wireless channel transmission simulations in typical mountainous environments are carried out using Wireless Insite software.A large amount of empirical data is obtained from the simulation,and the mathematical relationship between the transmission path loss and the distance between transceivers in these environments is obtained by data fitting,and the wireless channel propagation model in the corresponding environments is established,which final y forms an empirical data set and provides propagation model support for the subsequent deployment and site selection.The second part is to establish the mathematical model of optimized deployment of two communication sites for two optimization cases,combining the objectives of deployment site selection optimization in mountainous environment.The two optimization scenarios include:one is to provide a deployment scheme in which the minimum number of communication stations can cover all test points when the number of communication stations is unlimited;the other is to provide a deployment scheme in which the maximum number of test points can be covered when the number of communication stations is determined.In the third part,the algorithm for solving the optimal deployment mathematical model is studied,and the GD-MOPSO algorithm is proposed.The algorithm is designed based on the grid idea,using a combination of dominant accumulation strategy and shortest grid distance to select the leader,with the aim of obtaining a better Pareto solution,jumping out of the local optimum,and speeding up the convergence of the algorithm at a later stage.Finally,the effectiveness of the algorithm is il ustrated by comparing the performance with others.Finally,the GD-MOPSO algorithm is used to solve the two optimized placement mathematical models for three typical mountain environments,combined with the constructed empirical data set,and the final result is the placement scheme that satisfies the conditions.The results are compared with those of other algorithms,which again prove the effectiveness and practicality of the chosen deployment scheme by the method of this paper.