期刊
IEEE INTERNET OF THINGS JOURNAL
卷 9, 期 15, 页码 13153-13167出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3142206
关键词
Wireless communication; Wireless sensor networks; Internet of Things; Communication system security; Data communication; Wireless networks; Energy harvesting; Intelligent reflecting surface (IRS); Internet of Things (IoT); phase shifts; Stackelberg game; wireless caching; wireless-powered communication networks (WPCNs)
资金
- Engineering and Physical Sciences Research Council (EPSRC) [EP/P03456X/1]
- National Natural Science Foundation of China [61901327, 61941105, 62101499]
This article proposes an intelligent reflecting surface (IRS)-enabled wireless-powered caching system. The system utilizes wireless energy from a power station (PS) to deliver information from IoT devices to an access point (AP), with the AP storing the data in a local cache. The inclusion of the IRS enhances the performance of the wireless energy and information transfer process.
In this article, we propose an intelligent reflecting surface (IRS)-enabled wireless-powered caching system. In the proposed IRS model, a power station (PS) provides wireless energy to multiple Internet of Things (IoT) devices, delivering their information to an access point (AP) by utilizing the harvested power. The AP, equipped with a local cache, stores the IoT data to avoid waking up the IoT devices frequently. Meanwhile, we deploy the IRS involving in the wireless energy and information transfer process for performance enhancements. In this practical system, the PS and AP could belong to different service providers. Also, the AP requires to incentivize the PS to offer a provisional energy service. We model the interaction between the PS and AP as a Stackelberg game that jointly optimizes the transmit power of the PS, the energy price, the phase shifts of the wireless energy transfer (WET) and wireless information transfer (WIT) phases, as well as wireless caching strategies of the AP. In this way, we first derive the optimal solutions of the phase shifts and the transmit power of the PS in a closed form. We propose an alternating optimization (AO) algorithm to optimize the wireless caching strategies and the energy price iteratively. Finally, we present various numerical evaluations to validate the beneficial role of the IRS and the wireless caching strategies and the performance of the proposed scheme compared with the existing benchmark schemes.
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