An MIMO Configuration Mode and MCS Level Selection Scheme by Fuzzy Q-Learning for HSPA(+) Systems
In this paper, we propose a fuzzy Q-learning-based MIMO configuration mode and MCS level (FQL-MOMS) selection scheme for high speed packet access evolution (HSPA(+)) systems. The FQL-MOMS selection scheme intends to enhance the system throughput under the block error rate (BLER) requirement guarantee. It will determine an appropriate MIMO configuration mode and MCS (modulation and coding scheme) level for packet data transmission in HSPA(+) systems, under the situations that the channel status is varying and the channel quality indication (CQI) has report delay. The FQL-MOMS scheme considers not only the reported CQI and the last transmission result but also the BLER performance metric and the transmission efficiency. Moreover, it is effectively configured, where the fuzzy rules and the reinforcement signals for the Q-learning algorithm are sophisticatedly designed. Simulation results show that the proposed FQL-MOMS scheme increases the system throughput by up to 49.3 and 35.9 percent, compared to the conventional adaptive threshold selection (ATS) scheme [12] and the Q-HARQ scheme [14], respectively, under the BLER requirement fulfillment.
mimo mcs q-learning hspa(+) bler harq fuzzy logic