Multiple antenna wireless communication systems over MIMO channels

Abstract

The purpose of the present work is to investigate the advantages of utilizing multi-antenna systems on the capacity of wireless communication systems. This is explicitly due to their capabilities to overcome the impairments of wireless communication systems such as multipath fading and interference. The optimization tasks are carried out via the proliferating global evolutionary techniques to demonstrate their robustness in solving different antenna problems. Different approaches to demonstrate the ability of a linear array of antennas to reduce and/or reject interferences are adopted. First, null placement and sidelobe level reduction are challenged through excitation finding based on the Schelkunoff method and with the aid of genetic algorithms. Next, Particle swarm optimization is used for sidelobe level reduction in nonuniformly spaced linear arrays. Third, it is attempted to incorporate null placement flexibility to the Dolph-Chebychev arrays via position perturbation using Taguchi optimization method. Finally, MIMO system capacity maximization is sought. The purpose is to exploit the dependence of the MIMO channel characteristics on the inter-element spacing between the antennas in linear arrays. Existing models that take into account either signal correlation or mutual coupling effects have been used with a new channel model being proposed to account for both effects simultaneously