Abstract
With the development of wireless sensor network (WSN), the design and maintenance of WSN are still challenge in a large number of sensor nodes which are constrained in energy and bandwidth. Thus, a new solution is high altitude platforms (HAPs) that can be employed as the relay nodes of WSN in order to reduce the energy consumption of sensor nodes because of multi-hop relay transmission and to enlarge the coverage range of WSN. In this paper, a novel heterogeneous WSN system consisting of HAP layer, WSN layer and mission layer is proposed. In the system, we model a deployment model of HAPs based on markov random field with maximum a posteriori probability (MAP) framework, thus obtaining the energy function of HAPs. Then, a potential game approach is introduced to analyze the energy function, which proves to be able to achieve a pure Nash equilibrium. In addition, a modified distributed learning algorithm called sequential spatial adaptive play is presented to solve the proposed potential game. Finally, simulation results illustrate that the proposed method can achieve Nash equilibrium and the optimal deployment of HAPs.