Browsing by Author "Huang, Chiao-Yin"

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An Intelligent HARQ Scheme for HSDPA
(2011-05-01)
Huang, Chiao-Yin
;
Chung, Wen-Ching
;
Chang, Chung-Ju
;
Ren, Fang-Ching
;
電機工程學系
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%.
Fuzzy Q-Learning-based Hybrid ARQ for High Speed Downlink Packet Access
(2009)
Huang, Chiao-Yin
;
Chung, Wen-Ching
;
Chang, Chung-Ju
;
Ren, Fang-Ching
;
電信工程研究所
In this paper, a fuzzy Q-learning-based hybrid automatic repeat request (FQL-HARQ) scheme is proposed to enhance the system performance of high speed downlink packet access (HSDPA) in universal mobile telecommunications system (UMTS). In the HSDPA system, it is an important issue to choose modulation and coding scheme (MCS) for new data packet when channel quality indicator (CQI) is inaccurate. Hence, the purpose of the FQL-HARQ scheme is to determine a suitable MCS for new data packet so as to maximize the system throughput while guarantee the block error rate (BLER) requirement. In the FQL-HARQ scheme, the fuzzy logic is used to choose a suitable MCS for each new data packet. According to the feedback information from the HSDPA system, the Q-learning algorithm is adopted to update fuzzy rule base. This makes the FQL-HARQ scheme can adapt to the variation of environment. Simulation results show that the proposed scheme can increase the system throughput of up to 70 % compared to the conventional adaptive method in the case with CQI report delay.