Joint Sensing and Computation Offloading for Wireless Powered Mobile Edge Computing System

Mobile-edge computing (MEC) and wireless power transfer (WPT) are promising paradigms in the Internet of Things (IoT) era to alleviate limitations of energy and computation capacity of wireless devices (WDs). In this paper, we consider a wireless-powered MEC in which one hybrid access point (HAP) with a stable energy supply and computation capacity coordinates with a set of WDs with WPT and sensing capabilities. In the considered model, WDs first harvest RF energy transmitted by HAP and then sense data with stored energy for multiple sensing tasks. With MEC, WDs can execute tasks locally or offload data to HAP. To minimize the average latency, we formulate a joint sensing and processing optimization problem in a wireless powered-MEC system under energy and successful sensing probability constraints. This NP-hard problem can be decoupled into three subproblems. Then, we adopt an alternating algorithm to iteratively solve the WPT time, sensing time, and offloading policy subproblems. Simulation results demonstrate the effectiveness of our proposed joint optimization algorithm.