Research On MIMO Signal Recovery Method Based On Deep Learning

The wireless communication system is composed of a transmitter and a receiver,and the information is transmitted through the antenna after channel coding,modulation and other processing.Due to the influence of channel fading,noise and interference,the signal will have serious distortion,and the receiver needs to recover the original information as much as possible from the distorted signal.A receiver algorithm for multiple-input multiple-output(MIMO)communication systems based on deep learning is proposed.The deep neural network is used to replace the entire information recovery link at the receiver side to achieve bit information recovery.Compared with the traditional MIMO receiving algorithm,it can achieve lower bit errors.rate and better anti-interference performance.In summary,the main research contents and results of this paper are as follows:(1)Aiming at the high bit error rate of the traditional Alamouti algorithm in complex environments,a multi-label MIMO intelligent receiving algorithm based on deep learning is proposed to achieve the purpose of recovering the original bit information from the received signal,replacing the traditional physical communication layer.The entire information recovery process at the communication receiver end can overcome factors such as wireless channel fading,noise,and interference as much as possible.Experiments show that a lower bit error rate can be obtained under the Rayleigh channel.(2)The current research based on deep learning signal receiving algorithm is only suitable for the signal receiving of small-bit data.In order to meet the needs of receiving largerbit signals,a MIMO intelligent receiving algorithm based on multi-output classification is further proposed.A multi-parallel sub-network structure is designed,each sub-network realizes the recovery of one-bit information,and solves the problem of high bit error rate when the number of bits of bit information increases by using the multi-lable receiving method.The experimental results show that,The bit error rate performance of the received 128-bit signal is better than that of the Alamouti algorithm.(3)In order to solve the problem of high bit error rate of MIMO in mine environment,a mine MIMO intelligent receiving model is proposed.The model is based on the multi-tag MIMO intelligent receiving algorithm to realize the recovery of the original bit information.Compared with the traditional MIMO receiving algorithm,the model does not have the error accumulation caused by decoding,demodulation and other processes.The experimental results show that the model has a lower bit error rate than the traditional receiving method under different modulation,coding,number of transmitter antennas and other scenarios.In addition,it is proved that when there is a certain loss of received data,the model can still achieve effective reception and restore the original information.