{'fraction_non_alphanumeric': 0.025231286795626577, 'fraction_numerical': 0.00672834314550042, 'mean_word_length': 5.134020618556701, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Low Complexity Decoding Algorithm for Spinal Codes with Efficiently Distributed Symbols

A fast decoding algorithm with an efficientdistribution of symbols (EDS) for spinal codes is proposed in this paper. Firstly, the EDS decoder takes a grouping method to improve the efficiency of the distributed symbols through getting rid of the interference from the other groups. Then by taking the method of enhanced sequence decoding algorithm, the decoder has the ability to achieve dynamic search scope of nodes where it visits the flexible number of nodes in each decoding unit according to the real-time channel conditions. When compared with the Bubble algorithm, the unequal error protection (UEP) decoding algorithm, and the forward sequence decoding (FSD) algorithm, the proposed EDS algorithm obtains a better coding gain, significantly reduces the number of nodes visited, and achieves a rate (the bandwidth efficiency) closer to the capacity of the channel. Simulation results show that the rate of the proposed algorithm has a gain of 6%~15% and the complexity decreases by more than 70% when compared with the Bubble algorithm for the signal-to-noise ratio (SNR) range of 0~ 30 dB.