基于混合算法的多目标异构无线网络室内规划

新的无线网络技术设备的发展使得多种无线技术共存的异构无线网络渐渐的替代了单一技术构成的同构无线网络。为了获得高覆盖、低成本与低辐射的室内异构无线网络，本文提出了一个遗传算法与类粒子群算法相结合的混合算法。这个算法具备遗传算法搜索的广度及类离子群算法搜索的深度，获得并且避免了过早收敛于局部。算法被应用于多目标异构无线网络的规划中，仿真结果证明这个混合算法能有效的实现了多目标的无线网络规划方案的优化。

Multi-objective indoor heterogeneous wireless network planning based on the hybrid algorithm

The requirement of information interaction promotes the expansion of wireless networks. In the same period of time, development of new wireless network technologies and equipments results in a variety of wireless network architectures. As the result, the homogeneous network, which is composed of a single wireless network, is gradually replaced by the heterogeneous wireless network. This paper presents a hybrid algorithm combined the genetic algorithm with the quasi particle swarm algorithm. Improved genetic algorithm is used to search the breadth and depth, it also can avoid the premature convergence to the local optimal. The presented algorithm optimizes the multi-objective heterogeneous wireless network planning. The simulation results show that the hybrid algorithm can effectively achieve the multi-objective optimization (high coverage, low energy consumption and low exposure level) of the wireless network planning solution.