Electrical blind detection of coherent optical communication signals using feedback-voltage-bias-type Hopfield neural network

To solve the special issue of electrical adaptive blind equalization in wireless spatial diversity optical coherent receivers, a new blind detection algorithm of multi-value QAM signals using output-feedback-bias(OFB) type complex discrete-time continuous state(DTCS) Hopfield neural network was presented. The OFB will not change the traditional Hopfield model. The proposed OFB-DTCS Hopfield neural network can meet special requirement of the multi-valued signal detection which need enlarger the search space. The blind detection problem of multi-valued QAM signals was transformed into solving a quadratic optimization problem. How to map the cost function of this optimization problem to the energy function of OFB-DTCS Hopfield neural network was also shown. The proof, analysis and its constraints of the energy function were shown, respectively. A complex activation function to fit this special problem was discussed. Then a special connective matrix was constructed to ensure algorithm detect signals correctly. Finally, detailed simulation results and performance comparison with other algorithm were shown to demonstrate farther the effectiveness, superiority and shortage of this new algorithm.