Energy-Efficient Base Stations Locations Optimisation in an Airport Environment

Optimising the locations of base stations (BSs) is very challenging in highly dynamic environments such as airports, shopping malls and train stations where both spatial and temporal traffic variations are considerably high. Due to the continuous growth in international air traffic and the dynamic behaviour of passengers in an airport environment, providing reliable and cost effective communication facilities to passengers and staff becomes even more difficult at different times and locations. Using real measurements from Heathrow Terminal 4 (T4), we, in this paper, develop T4 passenger flow models which take both the spatial and temporal variations into account and help us accurately determine the traffic demand (TD), coverage area and path loss and thus outage and energy consumption. In this paper, we develop a multi-objective genetic algorithm (GA) which serves traffic demand and minimises both outage and energy consumption of the whole network. This eventually minimises the number of BSs while optimising their locations. To validate GA's results, a multi-objective mixed integer linear programming (MILP) model has been developed and both are found to be in good agreement. The results also reveal that only a few more base stations are required when we consider all three parameters together compared to the TD only case. However multiparametric objective function, considering TD, outage and energy consumption, consumes 100 times less transmission energy compared to the case of TD only while serving the same amount of traffic in such a dynamic environment.