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Machine-type communication (MTC) has been extensively studied to provide connectivity for devices and sensors in theInternet-of-thing (IoT). Thanks to the sparse activity, random access, e.g., ALOHA, is employed for MTC to lower signaling overhead. In this paper, we propose to adopt exploration for multichannel ALOHA by transmitting preambles before transmitting datapackets in MTC, and show that the maximum throughput can beimproved by a factor of 2 − e−1 ≈ 1.632, In the proposed approach, a base station (BS) needs to send the feedback informationto active users to inform the numbers of transmitted preambles inmultiple channels, which can be reliably estimated as in compressive random access. A steady-state analysis is also performed withfast retrial, which shows that the probability of packet collision becomes lower and, as a result, the delay outage probability is greatlyreduced for a lightly loaded system. Simulation results also confirmthe results from analysis.