Power Gain Pattern Synthesis via Successive Convex Approximation Technique

• Published in: IEEE access Vol. 8; pp. 181807 - 181814
• Main Authors: Yang, Feng, Yi, Duyu, Hu, Lingna, Zang, Guangda, Ding, Lianghui
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive beamforming; Algorithms; Antenna arrays; Approximation; Approximation algorithms; array pattern synthesis; Computational geometry; Convergence; Convex functions; Convexity; dynamic range ratio; Excitation; Mathematical analysis; Matrix converters; Mobile communication systems; Mutual coupling; Optimization; Power gain; power gain optimization; Satellites; Sidelobe reduction; Sidelobes; successive convex approximation; Synthesis; Upper bound; Upper bounds; wide main lobe beam
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3029034

Wide beam is necessary for ensuring the main lobe direction in a mobile communication scenario. A small dynamic range ratio (DRR) of excitations is crucial for simple-array and energy-saving design. The power gain pattern synthesis (PGPS) problem is aimed to maximize the minimum power gain in the wide main lobe and solving the PGPS problem can form a wide beam. To control the DRR, an upper bound constraint of DRR is imposed on the PGPS problem. The new problem is concave and can't be solved effectively by the conventional convex optimization method. We convert the DRR constraint into a group of stricter inequalities and transform the concave constraints to be convex with some convex approximations. The general PGPS problem with DRR constraints can be solved by the successive convex approximation (SCA) technique. The weights obtained by the proposed method can converge to the stationary point and we present the convergence proofs. Simulation results show that the proposed algorithm has better performance on increasing the minimum power gain in the main lobe (PGML) and suppressing the sidelobe level (SLL). Meanwhile, the DRR of excitations can be controlled below a given upper bound.