摘要
A sequence detector based on Hopfield Neural network(HNN) is presented, which is used to estimate the transmitted sequences from the received signals in mobile communications. In order to avoid the convergence of HNN in local minima, a decreasing step algorithm (DSA) is proposed to search the optimum sequence quickly on the basis of the traditional simulated annealing (SA) algorithm. Computer simulation results show that the new HNN detector provides almost the same performance as that of the Viterbi detector while needs less computations and memory capacity, thus it is more feasible in hardware implementation and long constraint convolutional decoding.
A sequence detector based on Hopfield Neural network(HNN) is presented, which is used to estimate the transmitted sequences from the received signals in mobile communications. In order to avoid the convergence of HNN in local minima, a decreasing step algorithm (DSA) is proposed to search the optimum sequence quickly on the basis of the traditional simulated annealing (SA) algorithm. Computer simulation results show that the new HNN detector provides almost the same performance as that of the Viterbi detector while needs less computations and memory capacity, thus it is more feasible in hardware implementation and long constraint convolutional decoding.
基金
National Natural Science Foundation of China
