Adaptive method of 5G PRACH peak detection algorithm

Abstract

The invention provides a self-adaptive detection method for a physical random access channel peak value of a wireless communication system. The self-adaptive detection method comprises the following steps: 100, determining whether random access leader sequence false detection occurs or not; 200, when it is determined that false detection occurs, solving the maximum value maxvalue and the average value mean from the collected average power of the power delay spectrums of all the random access preamble sequences, and calculating a noise factor and a noise threshold; and 300, detecting the random access preamble sequence by using the noise factor and the noise threshold. Based on the embodiment of the invention, the method can adapt to the change of a real 5G complex service scene, prevents the physical layer software of the base station from being caught in the cycle of repeatedly receiving the random access preamble sequence, reduces the deployment difficulty of the physical layer signal processing software, and adopts some specifically designed data structures in the implementation process. The occupation of memory resources is reduced.

Description

technical field [0001] The present application relates to the field of wireless communication technologies, and in particular to an adaptive method for a 5G PRACH peak detection algorithm. Background technique [0002] With the development of mobile communication technology, many existing applications have high requirements for wireless connection and uplink synchronization, including various tasks such as smart home and telemedicine. As a key step in establishing a wireless connection, Physical Random Access Channel (PRACH) has attracted much attention. The peak detection algorithm for access preamble in random access channel has always been a hot issue in wireless communication. The research on the peak detection algorithm mainly includes how to reduce the calculation amount of the system algorithm, the setting of the detection threshold and the improvement of the effectiveness of the detection algorithm in different scenarios. The traditional random access peak detectio...

AI Technical Summary

Problems solved by technology

The existing literature mainly studies the detection threshold setting rules in the peak detection algorithm from a static point of view. It does not fully consider the complexity of wireless communication business scenarios, and it is difficult to adapt to rapidly changing complex channel conditions. When the noise detection threshold cannot adapt to the new environment conditions, it is difficult to adjust in real time, resulting in problems such as false detection

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