Convex Optimization-Based Sidelobe Control for Planar Arrays

The changes of paradigm from "connected things" to "connected intelligence" is anticipated to be made possible by sixth-generation wireless systems, which increases the demand for extremely effective intelligent algorithms. When used in realistic sixth-generation applications, traditional optimization-based techniques typically suffer from low performance and high computing costs. In addition to computational time, interference is another non-negligible element that limits these applications’ performance. To cope with high time-consuming issues and interferences, in this paper, a convex optimization-based approach to synthesize antenna array patterns with controlled sidelobe levels will be proposed. In this approach, interferences are suppressed by reducing sidelobe levels while maintaining the main lobe in the desired direction. The achieved performances of the proposed approach are demonstrated and compared to metaheuristics-based approaches through numerical simulations.