基于自适应猫群算法的多目标波束赋形

针对大规模阵列天线波束赋形中智能优化算法精度不高、收敛速度不快等问题,提出一种自适应猫群算法.在猫群算法的基础上,使其基本参数根据迭代次数及适应度函数值自适应改变,并在搜寻模式中加入赌轮盘和精英选择相结合的策略,以增加种群多样性.多种智能优化算法的性能仿真对比分析表明,自适应猫群算法具有快速收敛、全局寻优的能力.将该算...

Max-min fairness-based resource allocation algorithm for heterogeneous VLC/RF networks

Aiming at the problems of low accuracy and low convergence speed of intelligent optimization algorithm in beam shaping for large-scale array antenna, we present a multi-objective beam shaping algorithm based on adaptive cat swarm algorithm. Based on the cat swarm algorithm, its basic parameters are adaptively changed according to the number of iterations and fitness function values, and a strategy combining roulette and elite selection is added to the search mode to increase the population diversity. The performance simulation and comparison analysis of several intelligent optimization algorithms show that the adaptive cat swarm algorithm has the ability of fast convergence and global optimization. Finally, the algorithm is applied to the multi-target beam shaping of 2×8 array antennas. The simulation results show that the adaptive cat swarm algorithm can effectively improve the efficiency and accuracy of multi-target beam shaping for array antenna.