Abstract
We investigate a reconfigurable intelligent surface (RIS)-aided wireless powered mobile edge computing (MEC) network, where a new RIS-aided hybrid non-orthogonal multiple access (NOMA) offloading scheme is proposed to improve the efficiency of both MEC offloading and energy harvesting. A joint optimization framework for the transmit power, time allocation, and RIS phase shifts is developed to minimize the overall energy consumption of the network, subject to the energy causality and MEC offloading constraints. Despite of the optimization problem's non-convexity with highly coupled optimization variables, we devise a computationally-efficient algorithm to solve it iteratively. Simulation results are also provided to facilitate the performance evaluation of the RIS-aided wireless powered MEC, quantify the value of the RIS for energy efficient MEC offloading, and validate the performance gains of the proposed hybrid NOMA offloading over various baseline schemes.
| Original language | British English |
|---|---|
| Title of host publication | 2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350329285 |
| DOIs | |
| State | Published - 2023 |
| Event | 98th IEEE Vehicular Technology Conference, VTC 2023-Fall - Hong Kong, China Duration: 10 Oct 2023 → 13 Oct 2023 |
Publication series
| Name | IEEE Vehicular Technology Conference |
|---|---|
| ISSN (Print) | 1550-2252 |
Conference
| Conference | 98th IEEE Vehicular Technology Conference, VTC 2023-Fall |
|---|---|
| Country/Territory | China |
| City | Hong Kong |
| Period | 10/10/23 → 13/10/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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