Dynamic multi-user computation offloading for wireless powered mobile edge computing

The combination of mobile edge computing (MEC) and wireless energy transfer (WET) has been recognized as a prominent solution to liberate massive wireless devices from limited battery capacities and compute-intensive workloads in the Internet of Things (IoT) environment. This new paradigm is called wireless powered mobile edge computing (WP-MEC). In this paper, an online computation rate maximization (OCRM) algorithm for multi-user WP-MEC systems is proposed by jointly managing the radio, computational resources, allocating time for energy transfer and data transmission. In each time block, the optimal bandwidth allocation and data transmit powers for offloading are achieved by Bisection method with linear time complexity. In addition, the closed-form solutions of optimal time allocation and CPU-cycle frequencies of wireless devices are obtained. The theoretical performance analysis shows that the time average sum computation rate and task queue backlog obey an [O(1/V), O(V)] tradeoff. Numerical results verify that, our proposed OCRM algorithm outperforms the baseline schemes without joint optimization, which dramatically improves the computation rate while making the system stable.