Coding and decoding method for rateless Spinal code based on Latin square

Abstract

The invention discloses a coding and decoding method for a rateless Spinal code based on a Latin square. The method comprises the following steps of generating an initial sequence; generating a statesequence; coding the state sequence by using a repeated Hadamard matrix; generating a parity bit sequence; generating all possible state code block sets; generating a possible initial code block; generating a full-connection grid diagram; decoding all possible state code block sets; selecting a decoding result by a decoder; judging whether a decoding sequence is the same as the initial sequence ornot; and outputting the decoding sequence selected by the decoder. According to the method, the Latin square is used for mapping each initial code block in the initial sequence and one adjacent initial code block into one state code block having the same length as the initial code block, so that the decoding calculated amount is reduced, the decoding complexity is reduced, and the decoding efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a coding and decoding method of a rateless Spinal code based on Latin squares in the technical field of wireless communication channel coding. The invention can be used for coding and decoding the rateless Spinal code. Background technique [0002] Rateless Spinal codes are rateless codes suitable for time-varying channel wireless networks, and are good codes that approach Shannon's capacity limit and are suitable for wireless communications. The core of the rateless Spinal code is to continuously use the pseudo-random hash function combined with the constellation point mapping function on the input information bits to generate the transmission symbol information. Excellent anti-interference performance. The existing rateless Spinal code decoding method is Bubble decoding, which is a maximum likelihood decoding scheme based on tree search. [0003] Xidian Universit...

AI Technical Summary

Problems solved by technology

However, the disadvantage of this method is that since the method uses the approximate maximum likelihood decoding algorithm for segmented tree search, the length of the hash state sequence will increase exponentially with the increase of the decoding tree depth. Increase the amount of calculation for decoding and increase the cost of decoding

However, the disadvantage of this method is that the forward state sequence and the backward state sequence obtained by mapping the information sequence using the hash function are too large, which increases the difficulty of decoding to obtain the state sequence and makes the decoding more complex.

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