北京航空航天大学学报 Journal of Beijing University of Aeronautics and Astronautics ISSN 1001-5 DOI: .1001-5965. Stack-bucket Algorithm for Convolutional Codes Based on Dynamic Optimization Regulation ZOU Wenliang, JIANG Yuzhong , HUANG Zhi, NIU Zheng, LIU Gang (School of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China) *E-mail: ******@ Abstract Long constraint length convolutional codes are used in the fields of satellite communication due to their strong anti-interference and difficult to decipher. However, in a low signal-to-noise ratio environment, there are shortcomings of low space utilization and high decoding complexity. To overcome the above problems, this paper proposed a stack -bucket algorithm (DORSB) based on dynamic optimization regulation. The algorithm uses a new parameter depth factor to assist path access, which can increase the path advantage near the end of the code tree and reduce the decoding complexity. When the stack overflows, the size of the bucket is regulated to reuse the bucket space and reduce the frame error rate, which can effectively improve the space utilization. The simulation results show that when the depth factor increment is appropriate and the fra
