Resource Allocation for Full-Duplex Wireless Information and Power Transfer in Wireless Body Area Network

The purpose of a wireless body area network (WBAN) is to collect and send vital body signals to the physician to make timely decisions, improve the efficiency of medical informatics systems, and save costs. The sensors of the WBAN network have limited size and energy, and hence, to extend the lifetime of these sensors, they can be powered wirelessly. Our focus in this paper is on a two-tier full-duplex (FD) cooperative WBAN in which sensors, in addition to transmitting physiological information, harvest energy from radio frequency (RF) coordinator signals and body sources. Our goal is to maximize average weighted sum throughput (AWST) under the constraints of each sensor, including meeting the minimum data rate, delay limitation, energy and transmission power constraints. The resources allocated to solve this optimization problem are the time slots, the transmission rates of the sensors and coordinator, and the transmission powers of sensors in each time slot. The time scheduling problem in the first step is modeled in the form of a mixed-integer linear programming (MILP) problem and the second step problem is convex. Also, Karush–Kuhn–Tucker (KKT) conditions are presented for power and rate allocation. In the optimal allocation (OA) mode, contrary to the equal time allocation (ETA) one, with increasing the relay power, the AWST increases despite increasing self-interference (SI). Energy harvesting from the body, nevertheless the power consumption for transmission, makes positive the slope of the instantaneous energy curve for the motion sensor and reduces the corresponding slope for the electrocardiogram (ECG) one. Comparison of the proposed method with previous methods shows that the proposed method has better control over the information flow of sensors, and also in allocating rate to users, fairness is satisfied. According to the simulation results in our method, the system showed better performance than the equal time allocation mode. We also used the FD technique and with the help of the optimal time scheduling index, we were able to control the SI.