量子遗传算法优化RBF神经网络的MIMO-OFDM信号检测研究

he optimal solution of signal detection is a NP(Non-deterministic Polynomial-time hard)problem. Aimed at the problems that RBF(Radial Basis Function) neural network is prone to the local optimum and simple genetic algorithm has the shortcoming of slow convergence, it shows a way that combines neural network with genetic algorithm. It makes use of genetic algorithm to optimize the initial data of the neural network., Quantum computation operation is presented in the course of optimization. And the algorithm is applied into the MIMO-OFDM detection systems. Using this algorithm, the output of detector by the QGA as the input of detector by the RBF neural network to avoid the bit -error rate for selecting initial data randomly and improve further the detection property. The result of the experiments shows the method is good for the improvement of the detection rate, and reduction of bit -error rate.