Wireless Powered Cognitive-Based Mobile Edge Computing With Imperfect Spectrum Sensing

Most mobile edge computing (MEC) works assume that the mobile devices (MDs) can offload their tasks to the MEC-severs at anytime, which may not be a practical assumption due to the tension between a large number of MDs and the scarce spectrum resources. In this paper, a framework for wireless powered cognitive radio (CR)-based MEC-enabled networks is proposed, which integrates three technologies: MEC, CR, and wireless power transfer (WPT). CR technology with imperfect spectrum sensing is adopted by the MD to find the spectrum access opportunities. An optimization problem is formulated to maximize the average calculated number of bits (CNoB) of the MD, which is non-convex and hard to solve. A two-loop procedure using a one-dimensional line search method is proposed. The time for spectrum sensing, WPT, energy harvesting (EH) and offloading, the central processing unit (CPU) frequency, and the transmit power of the MD are jointly optimized. Some semi-closed form solutions are obtained through Lagrangian dual decomposition and successive pseudo-convex approximation (SPCA) methods. Simulation results are presented to show the effectiveness of the proposed CR-based MEC scheme with different parameters.