基于粒子群优化的频域多信道干扰对齐算法

针对频域干扰对齐系统解空间的多峰值特性，提出了一种基于粒子群优化，以系统网络和速率为优化目标函数的干扰对齐全局搜索算法.该算法通过对速度向量在位置向量的法平面上做投影以加强全局搜索能力，并在粒子群标准位置更新的基础上增加沿目标函数梯度方向的学习搜索来提高算法收敛速度和趋向全局最优值的能力.数值仿真结果表明，该算法可以获得比现有算法更好的网络和速率性能.

On Particle Swarm Optimization for Multi-Frequency Channel Interference Alignment

For multi-frequency channel interference alignment( IA) system with single data stream trans-mitting for each user,the user solutions of capacities are important. However, there exist methods which can obtain optimal IA solution. Considering the complex multimodal characteristics of solution space of multi-frequency channel in LA system, a new gradient-exploited particle swarm optimization algorithm was proposed to search for the global optimal solution which directly takes the network sum rate as its ob-jective function. The capability for searching the optimal solution is enhanced by projecting the velocity vector on the normal plane of the position vector;the convergence rate is speeded through learning along the gradient of the network sum rate function. Numerical simulation shows that, the proposed method will obtain a better network sum rate performance than that of the existing algorithms.