## 1 Introduction  
Wireless body sensor networks (WBSNs) are a special case of wireless sensor networks (WSNs) that consist of multiple nodes to be attached to clothing, on the body or even implanted under the skin. Theirmain functionality is to sense, process and transmit a dataset of measured vital signals to a base station for the monitoring and the healthcare of chronic patients or the tracking of professional sportsmen's performance. In general, the sensor nodes used in these networks are tiny devices characterized by limited memory and processing resources, as well as strong battery power constraints. Therefore, an efficient use of resources is mandatory for maximizing the life time of sensors, while guaranteeing the good performance and high reliability of these networks. The power consumed by sensor nodes in a WBSN depends on the particular medical application and the transmission channel. According to the applications and depending on the measured variables, data transmission in WBSNs can require different sampling and data transmission rates. Therefore, for slow biosignals, sensor nodes transmit few data, and it is possible to reduce the energy consumption of the transceiver by turning it to the sleeping mode. However, if the biosignals are continuously time varying, sensor nodes transmit a larger volume of data, and hence, the power consumption of the transceiver will be increased. On the other hand, in a WBSN scenario, the human body plays an important role in the performance of the communication, where the on-body link can be highly dynamic due to the following reasons: (i) the human body introduces temporal variations in the quality of the wireless link, because body movements and postures can change the direction of the antennas, causing detuning and distorted radiation pattern [1]; (ii) it can also obstruct the propagation of the signal, causing non-line-of-sight (NLOS) conditions in an intermittent way [2]; (iii) it introduces attenuation due to the signal absorption by the tissue, dissipating heat [3,4]; (iv) it causes fluctuation in the path loss that can reach 30 dB on average [5]. Due the variability of on-body links and the application characteristics, the use of fixed transmission power can be inadequate. Then, data transmission at high power levels guarantees reliable links, but can result in an unnecessary energy waste. On the other hand, transmitting at low power levels provides energy savings, but at the expense of reducing the reliability and increasing retransmissions. Therefore, there is a trade-off between the energy consumption and the link reliability, and the transmission power should be adaptive in an energy-efficient fashion according to the current state of the link. The transmission power control techniques allow one to tune the power levels dynamically according to the changing conditions of the links. Therefore, these techniques allow meeting the reliability constraints, while at the same time saving energy. In this paper, we extend our previously proposed transmission power control algorithms ([6,7]) to a complex and realistic scenario. For that purpose, a state-of-the-art WBSN simulator has been upgraded with our model of the biologic channel and an efficient implementation of our reactive and predictive control techniques. The obtained results validate our optimization mechanism and show how our proposals can be used efficiently in deployed WBSNs, where the movement and position of the human subjects affect the transmission properties. Our main contributions are:  
* An extensive experimental data base of link quality metrics, which includes a human sample with diverse body features and different postures. * An extensive statistical analysis of the impact on the link quality metrics and their relation with the body shape and the body composition, from our experimental database. * An extensive validation by simulation of the transmission power control policies proposed, thanks to an enhanced version of the Castalia simulator.