Wireless-Powered OFDMA-MEC Networks With Hybrid Active-Passive Communications

• Published in: IEEE internet of things journal Vol. 10; no. 12; pp. 10484 - 10496
• Main Authors: Shi, Liqin, Chu, Xiaoli, Sun, Haijian, Lu, Guangyue
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.06.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Backscatter; Computation offloading; Computing time; Edge computing; Frequency division multiple access; hybrid active–passive communications; Internet of Things; Mobile computing; Modal choice; Nodes; OFDM; Optimization; orthogonal frequency division multiple access (OFDMA); Orthogonal Frequency Division Multiplexing; Quality of service architectures; Resource allocation; Resource management; Servers; Task analysis; Time-frequency analysis; Wireless communication; Wireless networks
• DOI: 10.1109/JIOT.2023.3241088
• ISSN: 2327-4662

In this article, we propose a novel system model for a wireless-powered mobile edge computing (MEC) network, where the Internet of Things (IoT) nodes perform partial offloading to the MEC server via hybrid backscatter communication (BackCom) and active radio (AR) following an orthogonal frequency division multiple access protocol, and maximize the system computation bits (SCBs). For the case of the system having more subchannels than IoT nodes, we formulate the SCB maximization problem that requires the joint optimization of the transmit power and time, subchannel allocation, computation frequency, and time of the MEC server, as well as the IoT nodes' BackCom time and reflection coefficients, transmit power and time for AR-based offloading, local computing time and frequencies, subject to the MEC server's computation capacity and the Quality of Service (QoS) and energy-causality constraints of each IoT node. By applying the proof by contradiction and time-sharing relaxation, we transform the formulated problem into a convex one and then solve it by using the existing convex tools. For the case of the system having less subchannels than IoT nodes, we propose a dynamic subchannel allocation scheme that allows each IoT node to choose one task-offloading mode from three modes: 1) HAPR; 2) BackCom only; and 3) AR only, while ensuring that no more than one IoT node occupies a subchannel at any time. The SCB is maximized by first determining the subchannel allocation and mode selection of each IoT node and then optimizing the remaining resource allocation for the MEC server and all IoT nodes under the obtained subchannel assignment and mode selection. Simulations validate the superior performance of the proposed schemes over several benchmark schemes from the SCB perspective.