Leveraging AI and Intelligent Reflecting Surface for Energy-Efficient Communication in 6G IoT
Qianqian Pan, Jun Wu, Xi Zheng, Jianhua Li, Shenghong Li, Athanasios, V. Vasilakos

TL;DR
This paper proposes an AI and IRS-enabled energy-efficient communication system for 6G IoT, optimizing power, phase shifts, and resource management to achieve low latency and energy consumption, validated through experiments.
Contribution
It introduces a novel AI-IRS integrated architecture and a DRL-based resource control scheme for energy-efficient 6G IoT communication.
Findings
Enhanced energy efficiency demonstrated in experiments.
Effective low-latency communication achieved.
Optimized resource allocation improves system performance.
Abstract
The ever-increasing data traffic, various delay-sensitive services, and the massive deployment of energy-limited Internet of Things (IoT) devices have brought huge challenges to the current communication networks, motivating academia and industry to move to the sixth-generation (6G) network. With the powerful capability of data transmission and processing, 6G is considered as an enabler for IoT communication with low latency and energy cost. In this paper, we propose an artificial intelligence (AI) and intelligent reflecting surface (IRS) empowered energy-efficiency communication system for 6G IoT. First, we design a smart and efficient communication architecture including the IRS-aided data transmission and the AI-driven network resource management mechanisms. Second, an energy efficiency-maximizing model under given transmission latency for 6G IoT system is formulated, which jointly…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · UAV Applications and Optimization · Optical Wireless Communication Technologies
