Multi-conflict detection method for random access channel of LTE power wireless private network

Abstract

The invention discloses a multi-conflict detection method for a random access channel of an LTE power wireless private network. An access detection unit performs the operations, such as receiving signal and base sequence cyclic correlation operation, binarization processing, noise elimination, waveform size adjustment, etc., on the acquired random access channel information; based on a convolutional neural network of deep learning, the coarse training and the fine training of a convolutional neural network detection model are realized, and a final convolutional neural network detection model is obtained, so that the convolutional neural network detection model detects the preamble of a random access channel and recognize the serious degree of the conflict. The method has the beneficial effects that the RACH conflict is detected by adopting the convolutional neural network based on deep learning, the existing protocol stack does not need to be modified, the conflict detection can be completed at the base station, the more accurate conflict detection performance can be obtained, the throughput of the LTE power wireless private network is improved, and the communication delay is reduced.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a method for detecting multiple conflicts in a random access channel of an LTE power wireless private network. Background technique [0002] In the LTE (Long Term Evolution) power wireless private network, the random access channel (Random Access Channel, RACH) process provides a synchronization mechanism between the base station (eNB) and the terminal equipment (TE), including four stages. Among them, the first stage is random access preamble: the terminal device requesting burst transmission randomly selects one from the available preamble set and sends it to the base station through RACH; the second stage is random access response (Random Access Response, RAR) : The signal received by the base station includes the superposition of preambles sent by all terminal devices, from which all preambles are detected, and a RAR message is sent for each detected preamble; ...

AI Technical Summary

Problems solved by technology

This method can control the probability of false detection at the cost of reduced performance of missed detection; although the threshold expansion method based on discretization can improve the performance of preamble detection, it will still increase the probability of missed detection

The preamble detection method with cascaded preprocessing units can improve the detection performance in low signal-to-noise ratio additive white Gaussian noise (AWGN) channels by preprocessing smooth noise before performing correlation operations, but it is not applicable to fading channels

In order to suppress the time dispersion of the frequency selective fading channel, the preamble detector based on multiple base sequences eliminates the interference signal in the original received signal, and the base station uses the power delay profile to extract the channel characteristic parameters, and then reconstructs the preamble signal, which can Identify non-orthogonal preambles and suppress noise in an interference-free environment, but calculating the power delay profile in real time consumes a lot of hardware resources and time overhead

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