Research of Beam Optimization for Multiple Feeds per Beam (MFB) Antennas Based on Genetic Algorithm

Multiple feeds per beam (MFB) antennas are currently one of the most popular solutions for modern high-throughput satellites (HTS). This paper presents an effective optimization method based on genetic algorithm for MFB antennas, which is composed of 7 feeds to composite one beam, namely "Medusa-like" configuration. Orthogonality constraints, introduced by lossless Beam Forming Network (BFN), are taken into account in overall optimization process. The optimized results for this type MFB antenna are given and shown good performances, with the gain, carrier to interference ratio (C/I) and cross-polarization discrimination (XPD) higher than 40.2dBi, 15.2dB and 22.6dB individually in each spot beam coverage.