Blind detection of QPSK signals using Hopfield neural network
Zhiyong Zhang, Yun Zhang · 2008
The paper proposes a new method to blindly detect QPSK signals of MIMO systems by using continuous Hopfield neural network (HNN). The new method successfully constructs a weighted matrix of HNN, which reduces the number of equilibrium points of HNN significantly, so that the speed to blindly detect signals is increased as well as the bit error rate (BER) is lowered. The new method detects multi-user signals with serial processing, in which the method utilizes those user signal vectors having been detected to extend the complementary subspace consisting of received data vectors in order to recover other user signals to be detected. The performance of the proposed HNN-based method is evaluated via computer simulations and compared with the existing approaches. Results are shown that the new method has better performances than others.