NOMA Assisted Energy-Efficient MEC for Environmental Severity Monitoring in Power IoT Networks: NOMA Assisted Energy-Efficient MEC

Guangmao Li; Gang Du; Hongbin Wang; Hongling Zhou; Jie Yang; Zhikai Pang

doi:10.4108/eetsis.8980

Authors

Guangmao Li Guangzhou Power Supply Bureau of Guangdong Power Grid
Gang Du Guangzhou Power Supply Bureau of Guangdong Power Grid
Hongbin Wang Guangzhou Power Supply Bureau of Guangdong Power Grid
Hongling Zhou Guangzhou Power Supply Bureau of Guangdong Power Grid
Jie Yang Guangzhou Power Supply Bureau of Guangdong Power Grid
Zhikai Pang Guangzhou Power Supply Bureau of Guangdong Power Grid

DOI:

https://doi.org/10.4108/eetsis.8980

Keywords:

NOMA, MEC networks, IoT networks, performance analysis

Abstract

This paper proposes an energy-efficient mobile edge computing (MEC) scheme that utilizes non-orthogonal multiple access (NOMA) for environmental severity monitoring in Power Internet of Things (IoT) networks. The primary objective of the proposed approach is to optimize energy consumption while ensuring tasks are completed within their respective deadlines and meet reliability constraints. The scheme integrates NOMA's superposition coding with mobile edge computing to improve task offloading efficiency and reduce computational delays. To achieve this, an iterative water-filling (IWF) algorithm is applied to dynamically adjust the power allocation for each task based on varying channel conditions and latency requirements. The optimization problem is formulated to minimize energy consumption while respecting the given constraints, including outage probability and transmission rate. Simulation results demonstrate that the proposed IWF-based method significantly outperforms traditional schemes. For instance, under a stringent delay threshold of 10 ms, the IWF method reduces energy consumption by approximately 30\% compared to conventional approaches. Furthermore, even as the delay threshold increases, the IWF method consistently maintains a noticeable advantage, achieving up to 20\% lower energy consumption compared to other schemes.

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