Rate adaptation algorithm has an important role in the Wi-Fi network. It ensures that the nodes transmit at a suitable transmission rate with minimum packet errors on the receiving side. However, there are cases when the existing algorithms fail to adapt to the changes in the communication environment. In this paper, we propose a rate adaptation algorithm using a Deep Q-network (DQN), in which the DQN agent controls the transmission rate of a node in response to the communication environment. We also evaluate the proposed algorithm using the field-programmable gate array (FPGA) and software-defined radio (SDR). The experimental result shows that the proposed algorithm can adaptively select the suitable MCS and maintain the throughput.