.png){kind=icon}
返回
Joint Task Offloading and Resource Allocation for NOMA-Enabled Multi-Access Mobile Edge Computing
.png){kind=icon}
PRE
AI
DOI：10.1109/TCOMM.2020.3044085.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multi-access mobile edge computing (MEC) allows each user to offload partial task bits to multiple MEC servers via multi-access radio transmission, enabling the collaboration of edge computing. By leveraging the advantage of nonorthogonal multiple access (NOMA) in improving the transmission efficiency, it is expected to effectively reduce the energy consumption of users in multi-access MEC with the aid of NOMA. However, considering the co-channel interference of NOMA and computation collaboration among MEC servers, the joint task offloading and resource allocation is a challenging problem. In this article, with the objective to minimize the weighted sum energy of users, we first propose optimal task offloading and resource allocation algorithms for the special single-user (OTORA-SU) and general multi-user (OTORA-MU) cases, by exploiting the convex and layered structure of the formulated problem. Interestingly, it is found that the single user always preferentially offloads task bits to the MEC servers with better channel gains, regardless of the computation capacity of each MEC server. Then, a low-complexity algorithm (LTORA-MU) is proposed for the general multi-user case, which converges fast and achieves near-optimal performances. Considering the channel estimation error, the impacts of imperfect channel state information (CSI) and successive interference cancellation (SIC) are also investigated. Simulation results demonstrate that for both perfect and imperfect CSI and SIC, 1) the proposed OTORA-SU and LTORA-MU outperform the local computing, full offloading, FDMA-based offloading and non-collaborative MEC schemes; 2) as the number of MEC servers grows, the ratio of offloading task bits increases while the energy consumption is decreased.
Keyword:
Task analysis
Servers
NOMA
Resource management
Collaboration
Energy consumption
Silicon carbide
Multiple radio access
mobile edge computing
nonorthogonal multiple access
resource allocation
task offloading
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8.3
论文数:
1.2W
被引数:
3.6W
机构
引用论文
分享收藏Cooperative Non-orthogonal Multiple Access With Simultaneous Wireless Information and Power Transfer
OAAI
OAAI分享收藏Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks5g异构网络中面向移动边缘计算的高能效卸载.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏分享收藏Energy-Latency Tradeoff for Energy-Aware Offloading in Mobile Edge Computing Networks移动边缘计算网络中能量感知卸载的能量-延迟权衡
PREAI
分享收藏
查看更多内容