A MIMO-SCFDE adaptive transfer method based on model-driven deep learning

Abstract

The invention relates to a MIMO-SCFDE adaptive transmission scheme based on model-driven deep learning. The invention establishes an adaptive transmission model based on the MIMO‑SCFDE system. AMNet and ADNet are used to replace the signal modulation and modulation identification parts in the traditional system respectively. AMNet adopts a combined network with 2D CNN, LSTM and FC-DNN as sub-networks to form an integrated neural network model, and adjusts the modulation mode of the sending end according to the channel conditions of the receiving end, and inputs the feature information extracted from the received signal into multiple sub-networks , and realize the conversion of features and optimal modulation schemes according to the network parameters obtained through training. At the same time, the received power under different path delays is selected as the adaptive factor to realize the adaptive integration of the results of each sub-network. According to the cyclic spectrum, ADNet has the advantage of accurately detecting the signal type under low signal-to-noise ratio, and based on the complexity of the cyclic spectrogram, it completes the adaptive selection of the modulation recognition scheme. This system is more suitable for the performance requirements of the 5G communication system.

Description

technical field [0001] The invention relates to the field of intelligent communication, in particular to a MIMO-SCFDE adaptive transmission method based on model-driven deep learning. Background technique [0002] Adaptive transmission technology refers to the technology that the transmitter of the system uses channel state information (CSI) to adaptively adjust the transmission strategy, including changing the transmission power, adjusting the modulation mode or adjusting the channel coding scheme, thereby improving the information transmission rate or reliability. Most of the traditional adaptive transmission technologies use complex algorithms to improve the performance of communication systems. However, for 5G communications that require high efficiency and high density, the increase in computational complexity will inevitably reduce the effectiveness of communications. With the rise of artificial intelligence technology, deep learning as an advanced data processing alg...

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Problems solved by technology

[0004] The present invention solves the problem of low throughput and reliability caused by the rule-based scheme in the adaptive transmission method of the existing multiple-input multiple-output single-carrier frequency domain equalization system (MIMO-SCFDE), and provides a method using AMNet and ADNet respectively To realize the adaptive transmission method for identifying the modulation mode of the signal to be transmitted and the modulation mode of the received signal

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