Active user detection and data decoding method of asynchronous massive machine type communication system

By adopting sliding listening window technology and message passing algorithm in asynchronous massive machine-type communication systems, combined with greedy search algorithm for delay calibration, the problem of degraded active user detection and data decoding performance caused by unknown user transmission delay is solved, and the accuracy and efficiency of detection and decoding are improved.

CN120675672APending Publication Date: 2025-09-19YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Patent Information

Application Number
CN202510839604.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-21
Publication Date
2025-09-19

AI Technical Summary

Technical Problem

In asynchronous massive machine-type communication systems, the performance of active user detection and data decoding is degraded due to the unknown user transmission delay.

Method used

A new receiver is adopted, combining sliding listening window technology and message passing algorithm. Through joint modeling, the detection and decoding of active users, channels and data under completely asynchronous conditions are realized. The delay calibration is updated using a greedy search algorithm, and the EM method is combined to perform joint active user detection, channel estimation and data symbol detection.

Benefits of technology

It simplifies the signaling overhead between the device and the access point, improves the performance of active user detection and data decoding, reduces the errors in channel estimation and data symbol estimation, and reduces the bit error rate and false detection probability.

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Abstract

The invention belongs to the technical field of information and communication, and relates to an active user detection and data decoding method of an asynchronous massive machine type communication system. Aiming at the problem that the detection and estimation performance is reduced due to unknown user time delay in asynchronous transmission, the method comprises the following steps: initial estimation and preprocessing: detecting initial active users and transmission time delay thereof through correlation peaks, and whitening received signals; the iterative joint detection and channel estimation module is used for iteratively updating channel information and data symbol information for multiple rounds based on a factor graph and a message passing algorithm; the data decoding module is used for decoding data based on a soft decision device; the detection and decoding performance is improved by transmitting external information among the modules; and the time delay parameter updating adopts a greedy search algorithm to obtain the optimal time delay. According to the method, the active user detection rate, the channel estimation precision and the data decoding accuracy under the condition that the receiving and transmitting ends are completely asynchronous are improved.
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