Abstract
Wireless body area network (WBAN) is composed of miniaturised sensors that operate in the vicinity of the human body for recording the vital physiological signals and wirelessly transmitting them to a central hub for further processing. In this study, a statistical approach is applied to an experimental channel data set to extract the models for the squared channel gain that best describe the characteristics of the transmission medium between the sensors and the central hub. The derived models are then utilised to investigate the error rate performance of WBAN sensors. On the basis thereof, an optimisation problem is formed for which the cost function is the symbol error rate (SER) metric. The constraints to be appended to the problem reflect the fact that the communication among the nodes is envisaged to be long-lasting and harmless to the human tissues. Depending on the way that the constraints are combined, four possible problems are defined. Subsequently, the method of Lagrange multipliers is deployed to find the closed-form expression for the optimal energy allocation that results in error rate minimisation. The numerical results cast light on the capabilities of the devised analytical framework and the insight that it provides into a WBAN operation.
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