A method for environment adaptive sensing wireless communication channel estimation and signal reconstruction

Abstract

The invention relates to an environment self-adaptation sensing wireless communication channel estimation and signal reconstruction method based on optimal recovery measurement induced by machine learning. The environment self-adaptation sensing wireless communication channel estimation and signal reconstruction method comprises steps that by using base station storage equipment, pilot frequency signals of time-space proximity, channel state information, and recovery measurement information are stored; a receiving end is used to receive the pilot frequency signals transmitted by a transmittingend, and by combining with the base station storage information, the machine learning method is adopted to realize the environment self-adaption sensing channel state and determine the optimal recovery measurement; the channel state information and the optimal recovery measurement are adopted to realize anti-interference, denoising transmission signal reconstruction. Based on the effective information stored on the communication base station and the machine learning principle, fast, effective learning, estimation, and elimination of influences of complicated noises on the wireless communication system can be realized, and therefore the robust estimation and the signal reconstruction of the wireless communication channels are realized in the same time or in shorter time by adopting the self-adaption way.

Description

technical field [0001] The invention relates to the fields of communication and machine learning, in particular to an environment adaptive perception wireless communication channel estimation and signal reconstruction method based on machine learning induced optimal recovery metrics. Background technique [0002] Accurate transmission of information has always been the primary goal of wireless communication. In a complex interference and noise environment, how to better eliminate interference and noise in communication and achieve more accurate communication is a key problem that needs to be solved urgently. In recent years, the development and maturity of machine learning-related theories, especially machine learning technology, has made it possible to innovatively apply machine-learning-related methods to solve the problem of accurate information transmission in wireless communication systems under complex interference and noise backgrounds. [0003] It is an inevitable tr...

AI Technical Summary

Problems solved by technology

[0004] In addition, the base station in the wireless communication system has to process a large amount of information every day, but it is not fully utilized at present, causing a large amount of valuable information to be wasted and lost.

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