{'fraction_non_alphanumeric': 0.03633916554508748, 'fraction_numerical': 0.0, 'mean_word_length': 5.098360655737705, '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}}
Design of Transmission Lengths for IR-HARQ Scheme Using Q- Learning

In this paper, we apply the Q-learning algorithm to design the transmission lengths of incremental redundancy hybrid automatic repeat request (IR-HARQ). The incremental redundancy (IR) bits are generated by polar codes with the polarizing matrix extension. The IR-HARQ scheme is considered as an environment, where the number of transmissions, the number of information bits, code rates, and signal-to-noise ratio (SNR) are the state of Q-learning. The reward is obtained by calculating the throughput of the successful transmission. The simulation results show that our Q-learning-based transmission lengths outperforms the fixed transmission lengths in the IR-HARO scheme.