Research Of Blind Detection Based On Immune Genetic Algorithm

The immune genetic algorithm is an improved genetic algorithm. It is based on the biologicalimmune mechanism. It has global search capability, mechanisms of diversity maintaining andstrong robustness characteristics of analoging and reflecting the biological immune system. Atpresent, it has been successfully applied in the fields of automatic control, bio-engineering, socialand economic. The blind detection technology does not need to send a training sequence, because itmakes an estimate only based on the received sequence. Blind signal detection has a wide range ofapplications in many scientific fields, particularly, in the field of wireless communication systemsand bio-signal processing. This paper gives direct blind signal detection, which is based on theimmune genetic algorithm, and then analyses algorithm performances. On top of this paper gives afurther improvement of this algorithm, showing that the improved algorithm has obvioussuperiority.This paper is organized as follows. The first chapter generally explains the background, statusof the study and the main work of this paper. The second chapter describes the principle of theimmune genetic algorithm and domestic and foreign scholars’ research in the immune geneticalgorithm. Chapter III illustrates basic theories which are about blind equalization technology andblind signal process. Chapter IV gives the model of blind signal detection which is based on theimmune genetic algorithm, simulates and analyses algorithm performances. Chapter V proposesblind signal detection based on chaos and immune genetic algorithm, simulates and analysesalgorithm performances. The work of this dissertation is summarized in chapter VI and theprospective of future research is also discussed in this chapter.