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In this paper, we propose an intelligent hybrid automatic repeat request (iHARQ) scheme for high-speed downlink packet access (HSDPA) systems. The challenge in the hybrid automatic repeat request (HARQ) control problem of HSDPA is how to choose an appropriate modulation and coding scheme (MCS) for initial transmission in the situation wherein the channel quality indication (CQI) has report delay. The iHARQ scheme will determine the suitable MCS to maximize the system throughput and guarantee the block error rate requirement in such an uncertain environment. By modeling the HARQ behavior as a Markov decision process, we adopt fuzzy logics to determine an appropriate MCS for each initial packet transmission. In addition, a Q-learning algorithm is utilized to update the fuzzy rule base, according to well-designed reinforcement signals fed back from the HSDPA system, such that the iHARQ scheme can adapt to the delayed CQI. Simulation results show that, compared with a conventional adaptive threshold selection method, the proposed iHARQ scheme increases the system throughput by up to 75.2%.