Design of Compact High-Isolation MIMO Antenna With Multiobjective Mixed Optimization Algorithm
Qianqian Li, Qing‐Xin Chu, Yu‐Lin Chang
Abstract
Integrating particle swarm optimization (PSO) and binary PSO into multiobjective evolutionary algorithm based on decomposition (MOEA/D) by group operator in parallel, an improved mixed optimization algorithm MOEA/D-M is proposed as an automation design scheme for compact high-isolation multiple-input-multiple-output (MIMO) antenna design. When the algorithm runs, each particle has several neighboring particles and all the particles are subdivided into a few groups. Both groups and neighborhoods provide helpful or potential information to their members. Then, under predefined constraints, MIMO antenna with anticipated performance can be generated intelligently and targetedly. The effectiveness of this design scheme is demonstrated by a single-band and a dual-band compact high-isolation MIMO antenna design for wireless local area network (WLAN)/world interoperability for microwave access (WiMAX) applications sharing the same initial reference model. The design degree of freedom of MIMO antennas may be increased greatly with the proposed design technique.