Research And Application Of Quantum Genetic Algorithm In Blind Detection

Accordanced with the received singal of the system and priori knowledge,the blind detectionalgorithm can achieve the data transmitted by the input terminal without the training data.Quantumgenetic algorithm is a global optimization algorithm that combines genetic algorithm principle andquantum theory.It has a search capability,short computing time and fast convergence speedadvantages.So it has been applied in many fields,but in blind detection field it is still blank.Fromthis point,the quantum genetic algorithm is applied to blind detection.In line with the shortcomingsof quantum genetic blind detection algorithm,this paper proposes two improved self-regulatingvariability quantum genetic blind detection algorithm.The main work of this paper is as follows:(1)This paper presents a quantum genetic blind detection algorithm.First, it establishes theblind detection mathematical model of the SIMO system.Then it constructes receiving matrixcomplement projection operator to get a evaluation function.Finally it is converted into a fitnessfunction in quantum genetic algorithm.So this paper uses the quantum genetic algorithm to find theoptimal result and detects a transmission signal of the system. The simulation experiments of thequantum genetic blind detection algorithm prove the superiority of algorithms.(2)Quantum genetic blind algorithm has been improved in this paper.It proposes two improvedalgorithms——self-adjusting quantum revolving door policy variation quantum genetic blinddetection algorithm and self-adjusting step quantum rotation angle variation quantum genetic blinddetection algorithm.Simulation results prove that both improved algorithm have good blinddetection performance, lower bit error rate and better performance than basic quantum genetic blinddetection algorithm.(3)This paper compares the time complexity of improved quantum genetic, basic genetic blinddetection algorithm and two improved algorithms.The results show that the time complexity of thequantum genetic blind detection algorithm is lower than the basic genetic blind detection algorithm.The two improved algorithms have the same order of magnitude with the quantum genetic blinddetection algorithm.The final conclusion shows that the proposed algorithms reduce the error ratebased on the low time complexity and improve the speed of convergence of the algorithm.