Research on anti-interference based on particle swarm optimization algorithm in high altitude platform stations

The future communication network will be composed of ground-based, sea based, air-based and space-based networks to build a distributed air, space and sea integrated global intelligent network across regions, airspace and sea areas. High altitude platform stations (HAPS) communication system combines the advantages of satellite and land communication systems, and effectively avoids their disadvantages. Artificial intelligence technology enables the wireless communication network, establishes the mathematical model of the wireless network according to the historical situation of the wireless network then trains the mathematical model and continuously optimizes the model, so as to obtain the optimal model, and then adjusts the model parameters according to the changes of the network in practice. The multi antenna system is mounted on the high-altitude platform stations to form multi beam to provide services for users. The beams between different the users will interfere with each other, which will affect the beam performance of high-altitude platform stations. This paper introduces an anti-interference algorithm based on particle swarm optimization. First we construct the anti-interference mathematical model of multi antennas system of high-altitude platform station. Then we train this model through particle swarm optimization algorithm. Finally, the performance of the algorithm is verified by simulation.