基于遗传算法的蜂窝广域空基伪卫星网络布局优化

Wide Area Cellular Network Layout Optimization of Air-Borne Pseudo Based on Genetic Algorithm

为能实现近地面大区域覆盖的多指标空基伪卫星网络的布局优化,提出了蜂窝波浪式伪卫星网络,并定义、分析了网络设计及优化的衡量指标。鉴于遗传算法大范围搜索能力弱、优化结果容易陷入局部最优等问题,因此对网络布局进行优化时,采用先由经验法粗略确定影响网络性能参数的取值范围,再用遗传算法在小区间内对网络性能指标进行多参数精寻优的方法,最后对优化后的网络性能进行研究分析。仿真结果表明:提出的蜂窝型波浪式网络优化后能实现广域覆盖,能保证服务区PDOP的可用性;通过对先用经验法后用遗传算法与直接用遗传算法2种方式网络优化性能的比较,还能得出前者能提高网络优化的效率及性能。

To achieve the layout optimization of multiple index air-borne pseudo satellite network of ground-level and large-scale coverage, the paper puts forward pseudo satellite network in cellular wave-mode, defines and analyses the measurable indicator of network design and optimization. Considering the weakness of wide-range search ability of genetic algorithm and the problem of the optimal result that is easy to fall into local optimum and so on, the suitable means of network layout optimization is that using empirical method to roughly determine the value range that affects network performance parameters, after that using genetic algorithm to conduct the multi-parameter optimizing on network performance indicators in small zones. Finally, research and analysis on performance of network which was optimized should be carried out. The simulation results show that the proposed cellular wave-type network can achieve wide area coverage and ensure the availability of PDOP in service area. By comparing the two approaches which are a combination of empirical approach first and genetic algorithm next and empirical approach merely and directly to optimize network performance, the conclusion can be achieved that the former approach can improve the efficiency and performance of network optimization.