Context recognition is a topic that has garnered considerable interest in the ubiquitous and pervasive computing research community. A wide variety of Internet-of-things devices with micro-electromechanical system (MEMS) sensors are used to obtain sensor data (e.g., acceleration, vibration, and sound) related to target contexts. However, devices for context recognition also have limitations such as deployment cost, battery maintenance cost, and the requirement for wearing/carrying the devices. To solve this problem, wireless sensing has attracted the attention of many researchers because it enables device-free and/or maintenance-free context recognition. In this study, we will comprehensively review studies on context recognition by wireless sensing, focusing on WiFi channel state information (CSI), radio-frequency identification (RFID), and backscatter. We will also discuss the design choices of wireless sensing with their pros and cons through a review of the state-of-the-art.