A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies.
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