Loader and Tester Swarming Drones for Cellular PhoneNetwork Loading and Field Test: Non-stochasticParticle Swarm Optimization

• 作者: Amir Mirzaeinia Mehdi Mirzaeinia Mohammad Shekaramiz Mostafa Hassanalian
• 来源期刊: 自主智能(英文)
• 学科: 工学
• 关键词: Particle Swarm OPTIMIZATION SWARMING DRONE Cellular NETWORK Radio OPTIMIZATION Loaded NETWORK Test
• 年，卷（期）: 2019,（2）
• 页码范围: 14-24
• 页数: 11页
• 分类号: TP3

摘要

Cellular network operators have problems to test their network without affecting their user experience. Testingnetwork performance in a loaded situation is a challenge for the network operator because network performance differswhen it has more load on the radio access part. Therefore, in this paper, deploying swarming drones is proposed to loadthe cellular network and scan/test the network performance more realistically. Besides, manual swarming dronenavigation is not efficient enough to detect problematic regions. Hence, particle swarm optimization is proposed to bedeployed on swarming drone to find the regions where there are performance issues. Swarming drone communicationshelps to deploy the particle swarm optimization (PSO) method on them. Loading and testing swarm separation help tohave almost non-stochastic received signal level as an objective function. Moreover, there are some situations that morethan one network parameter should be used to find a problematic region in the cellular network. It is also proposed toapply multi-objective PSO to find more multi-parameter network optimization at the same time.