摘要 : In this paper, we investigate two classification methods based on the significance and fairness of sensors in virtual multi-input multi-output (MIMO) wireless body area network (WBAN), where the access point (AP) with multi-antenn... 展开 In this paper, we investigate two classification methods based on the significance and fairness of sensors in virtual multi-input multi-output (MIMO) wireless body area network (WBAN), where the access point (AP) with multi-antenna provides energy to classified sensors placed on different parts of human body by broadcasting radio frequency (RF). In order to better characterize RF broadcasting channel, we use path loss model and model the link fading by a log-normal distribution. For two kinds of classified sensors., we adopt maximal ratio transmission (MRT) beamforming during wireless power transfer (WPT) phase, and zero-forcing (ZF) decoding for wireless information transfer (WIT) phase, respectively. Since that objective function is a non-convex optimization problem, we convert it to a convex function and solve it by CVX tool. Finally, simulation results demonstrate the reliability of the optimal solution. 收起