An Adaptive Partitioning Parallel MLFMA for Simulating Radome‐Enclosed Antenna Arrays

ABSTRACT Accurate and efficient simulation of large‐scale radome‐enclosed antenna arrays is challenging in the fields such as radar and communication. The parallel multilevel fast multipole algorithm (MLFMA) is suitable for solving radiation problems of large‐scale radome‐enclosed antenna arrays. To enhance the efficiency and balance the workloads for the MLFMA, this paper presents a parallel MLFMA framework. The proposed algorithm creates multiple MLFMA octrees for different medium regions and waveport excitations. In the parallel computation of near‐field interactions, an auxiliary octree is constructed to avoid the duplication of triangular integrals and employ the K‐way approach to partition the workloads. In the computation of far‐field interactions through evaluating the workloads related to each tree and dynamically partitioning the process groups, an adaptive partitioning strategy is designed to balance the workloads of multiple octrees, which reduces the communication traffic and achieves high parallel efficiency. Numerical results show that efficiencies of the parallel MLFMA are higher than 80% when the number of processes increases from 36 to 720.