Research On The Base Station Location Based On The Immune Algorithm

With the development of wireless communication technology and the emergence of smartphones, the users are becoming more and more high requirement of wireless internet service. Wireless service is mainly provided by the base stations which are set up by telecommunications companies. The choice of base station largely affect the quality of the services provided and the cost of the site. Meanwhile, with the emergence of 4G mobile phone and internet service, people need a lot of new base stations. Base station location is a multiple factors related issues, such as construction cost, range of coverage and signal quality. Reasonably for base station location can provide customers with comprehensive high quality network services, on the other hand, it can also reduce the cost and save resources for communication companies. So, how to make the base stations location reasonably and achieve high coverage rate with less cost is a problem need to be solved urgently.First, we analyze the important factors influencing the base station location based on the principle of base station in this paper, including geographical environment and demand factors. And they constitute the comprehensive environmental factors on site selection of base station. Then put forward a base station site model which can take consideration of the construction cost, range of coverage and the environment. Through the comparison in recent years for a variety of different methods to solve the problem of base station location and analysis of their characteristics and applicability, we finally chose the immune algorithm to solve the problem. Immune algorithm is a remarkable algorithm with good convergence. It can keep good solutions through the memory and ensure the diversity of the population.Further, applying the method in this paper to make the base station location for a given target area in Anshan area. In order to consider the geographical environment and demand factors in the first part of the research, we extract the actual site environment possible in this paper and using the associative classification data mining methods to obtain the comprehensive site environment and the establishment of the suitability classification association rules. Then use the rules to evaluate candidate sites is suitable for site condition which is applied to the first part of this paper research on the model. By comparing with existing research, the experiment result shows that the method put forward in this paper can get better location decisions in the real environment.