基于免疫算法的TD-SCDMA网络基站选址优化

Immune algorithm-based base station location optimization in the TD-SCDMA network

针对已有3G基站选址优化算法的不足和TD-SCDMA网络的特点,提出了一种基于免疫算法的TD-SCDMA网络基站选址优化方案。建立了基站选址问题的数学模型,设计了基于反学习的种群初始化方案和精英交叉策略,给出了免疫优化算法框架。实验结果表明,该算法不仅能够以较小的建站代价获得较高的网络覆盖率,而且算法具有较好的收敛性。

According to the defects of the existing 3G base station location optimization algorithms and the characteristics of the TD-SCDMA network, an optimization program was proposed for TD-SCDMA network base station location based on immune algorithm. A mathematical model of base station location was established. A population initialization program based on opposition-based learning and an elite crossover strategy were also designed, and the immune optimization algorithm framework was presented. The experiments＇ result shows that the algorithm cannot only get higher network coverage with a relatively smaller consideration, but also have better convergence.