Maximizing computation rate for NOMA-based WPT-MEC with user cooperation under nonlinear EH model

Over the past few years, the market size of the Internet of Things (IoT) has achieved a leapfrog growth. However, the large-scale data processing and the limited battery capacity of IoT devices have posed severe challenges to the existing IoT. To address this issue, mobile edge computing (MEC) technology and wireless power transfer (WPT) technology have been introduced, significantly reducing the computing pressure on IoT devices and achieving sustainable energy supply. To optimize the computing capacity of the IoT, this paper studies a wirelessly powered transmission mobile edge computing (WPT-MEC) system assisted by user cooperation (UC) and non-orthogonal multiple access (NOMA). A nonlinear energy harvesting (EH) model that is more in line with the actual energy collection process in reality has been adopted. By jointly optimizing the time allocation, transmission power, and power distribution across multiple energy beams at the HAP, the system’s weighted sum computation rate (WSCR) is maximized. To solve the proposed non-convex optimization problem, an iterative optimization algorithm based on successive convex approximation (SCA) is designed. Firstly, the non-convex optimization problem is reformulated using the variable substitution method to transform it into a more manageable form, and then SCA is applied to solve it. Numerical results illustrate that the proposed scheme can improve the overall performance of the system compared with the traditional benchmark schemes.