LEAL, I. A. C.; http://lattes.cnpq.br/7054209255136056; LEAL, Israel Aires Costa.
Resumen:
This thesis presents a methodology that uses bio-inspired optimization algorithms to increase
the channel capacity in Multiple Input Multiple Output (MIMO) systems considering
mutual coupling (MC) to promote a reduction in the distance among the array elements.
The method starts with the microstrip antenna design, at the frequency of 26 GHz, that
is used as a prototype for MIMO system testing and peformance analyses. The antenna is
simulated using the CST Studio Suite® software, and Genetic Algorithms (GA) are used to
optimize, to determine the antenna’s physical parameters and to improve its performance.
The method considers the MC among antenna array elements in the signal transmission
and reception. The Conventional Mutual Impedance Method (CMIM) and the Receiving
Mutual Impedance Method (RMIM) were chosen to be used in the simulation, because of
their adherence to real situations. The Particle Swarm Optimization algorithm (PSO) is
used to optimize the channel capacity and to reduce the distance among the elements with
a specific modification for the problem that uses particle in acceleration strategy in a specific
part of the search space. This thesis presents a method of analyzing the results in reception
mode as a function of channel capacity. Simulation results show that it is possible to obtain
a MIMO system performance improvement of 11.1% in channel capacity, and the distance
between elements can be reduced by 23.7%, considering the MC.
