Abstract
In digital communication systems, error correction codes are used to recover data that has been disturbed in a noisy environment. Convolutional code is a commonly used error correction code. In non-cooperative communication systems, it is very meaningful to blindly identify the synchronization position and coding parameters of convolutional codes. Existing reference had proposed a blind recognition algorithm for coding parameters of k/n rate convolutional codes in a noisy environment, but it didn't take into account the case where the received code words were not synchronized. In this paper, this problem is improved by using the quasi-correlation between the receive sequence and the check matrix to estimate the synchronization position, while obtaining the check matrix. It implements blind recognition of the synchronization position and coding parameters of k/n rate convolutional codes in a noisy environment. Simulation experimental results show that the improved algorithm in this paper is effective.
Highlights
INTRODUCTIONError correction coding is the most effective method to prevent the destruction of information
In digital communication systems, error correction coding is the most effective method to prevent the destruction of information
Ding et al.: Improved Blind Recognition Method for Synchronization Position and Coding Parameters case of k/n rate in [10], and the parameter recognition method of convolutional codes at arbitrary code rates was better achieved with lower computational complexity
Summary
Error correction coding is the most effective method to prevent the destruction of information. Ding et al.: Improved Blind Recognition Method for Synchronization Position and Coding Parameters case of k/n rate in [10], and the parameter recognition method of convolutional codes at arbitrary code rates was better achieved with lower computational complexity This was the first proposed algorithm that can completely realize the blind recognition of k/n convolutional codes in a noisy environment. An improved method is proposed to blindly recognize the frame synchronization positions and encoding parameters of all types of k/n convolutional codes in a noisy environment.
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