| Compared with terrestrial communication systems,the complex marine environment and the difficulty in installing communication equipment restrict the development of marine communication systems.The proposal of our country’s maritime power strategy puts forward higher requirements for the marine communication system The application of deep learning in the field of wireless communication is becoming more and more extensive.On this basis,the OFDM and FBMC signal detection algorithms in the marine environment based on densely connected networks are studied.The specific research contents are as follows:(1)Aiming at the problems of low bit error rate and strong dependence on cyclic prefix and pilot of traditional OFDM in the complex marine channel,an OFDM signal detection algorithm based on DenseNet is proposed,which is an end-to-end signal detection algorithm implemented by a network model.The DenseNet model is designed according to the structure of the OFDM,and it is used to replace all the functional modules of the receiving end of the communication system.The IQ signal received by the receiver is used as the data set,and the original baseband signal is used as the data label to train the network.Then use the test set to simulate and verify the model.Under the marine channel model,the proposed algorithm has better signal detection and recovery performance and less dependence on pilot and cyclic prefix.(2)Aiming at the problems of high computational complexity and bit error rate of traditional FBMC signal detection algorithm in the complex marine environment,an FBMC signal detection algorithm based on improved DenseNet is proposed.FBMC uses prototype filter on each sub-carrier to filter the signal.which increases the complexity of the signal structure and also increases the difficulty of the network model to extract useful features in the data set.The original DenseNet model is optimized using SE-Net,and the features that are beneficial to the training results are enhanced through weight distribution to improve the model performance.Under the Gaussian white noise and the marine channel models,compared with the traditional FBMC signal detection algorithm,the detection algorithm based on the DenseNet has better signal recovery performance and lower bit error rate.The optimized model can further improve the signal detection performance.Aiming at the problem that the use of OQAM modulation in FBMC combined with MIMO technology will seriously affect the signal detection performance of the receiving end due to the internal interference of the system,the above two network models are used to realize the signal detection of the FBMC-MIMO.The experimental results show that the internal interference of the system has little influence on the network model,and the network model has better signal detection performance in the FBMC-MIMO system. |
