MCV-facilitated Green Energy Far-field Wireless Charging for MEC Network

The rapid expansion of the Internet of Things (IoT) has led to the widespread deployment of IoT devices (IoT Ds) that enhance societal efficiency and convenience. However, these devices often face significant energy consumption challenges due to their computational tasks. Mobile Edge Computing (MEC) has emerged as a solution to offload these tasks, thereby reducing local energy consumption. Despite this, traditional energy supply methods remain inadequate for the vast number of IoT Ds. Far-field wireless charging, powered by green energy, offers a promising alternative but has not been extensively studied in conjunction with MEC. This paper proposes an integrated MEC and green energy far-field wireless charging network to address these issues. We develop energy consumption models for IoT Ds, Green Base Station (GBS), and Mobile Charging Vehicle (MCV), and formulate a problem to maximize the survival percentage of IoT Ds. Given the NP-hard nature of this problem, we introduce the Least Energy Loss (LEL) algorithm to optimize the number of MCV anchor points, thereby enhancing energy delivery to IoT Ds. Extensive simulations demonstrate that our proposed algorithm significantly improves the survival percentage of IoT Ds, validating its effectiveness.