Adaptive beamforming algorithm for interference suppression based on partition PSO

A novel adaptive beamforming algorithm for interference suppression based on Partition particle swarm optimization (PPSO) is presented. Firstly, the search phase space is divided into several parts, which makes it more suitable for parallel realization. Secondly, for each partition, a sub-swarm multidimensional particle is used to present weight vectors. It is updated by PSO to search the optimal solution. Finally, for each iteration, a whole-space global optimal solution, achieved by the minimum square error criterion, is achieved from all sub-space global optimal values of the sub-swarms. Our simulation results show that the proposed algorithm performs better than the traditional schemes both in convergence speed and the capability of avoiding local optima, and it is much more suitable for parallel realization.