IRS-Assisted Short Packet Wireless Energy Transfer and Communications

Bingxin Zhang; Kezhi Wang; Kun Yang; Guopeng Zhang

doi:10.1109/LWC.2021.3126596

IRS-Assisted Short Packet Wireless Energy Transfer and Communications

Bingxin Zhang, Kezhi Wang, Kun Yang, Guopeng Zhang^*

^*Corresponding author for this work

School of Computer Science

Research output: Contribution to journal › Article › peer-review

34 Citations (Scopus)

83 Downloads (Pure)

Abstract

In this letter, we analyse and optimize an intelligent reflecting surface (IRS)-assisted ultra-reliable and low-latency communications (uRLLC) system supported by wireless energy transfer (WET) technology, in which short packets are used in both the WET and wireless information transfer (WIT) phases. We first present the statistical features of the signal-to-noise ratio (SNR) of the system. Then, we derive an approximate closed-form expression of the average packet error probability (APEP). Additionally, we optimize the channel uses in the WET and WIT phases to maximize the effective throughput (ET) of the system. Finally, the effectiveness of the proposed solution is verified by Monte-Carlo simulation.

Original language	English
Pages (from-to)	303-307
Number of pages	5
Journal	IEEE Wireless Communications Letters
Volume	11
Issue number	2
Early online date	15 Nov 2021
DOIs	https://doi.org/10.1109/LWC.2021.3126596
Publication status	Published - 1 Feb 2022

Keywords

Average packet error probability
Effective throughput
Short-packet communications
uRLLC
Wireless energy transfer

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10.1109/LWC.2021.3126596

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title = "IRS-Assisted Short Packet Wireless Energy Transfer and Communications",

abstract = "In this letter, we analyse and optimize an intelligent reflecting surface (IRS)-assisted ultra-reliable and low-latency communications (uRLLC) system supported by wireless energy transfer (WET) technology, in which short packets are used in both the WET and wireless information transfer (WIT) phases. We first present the statistical features of the signal-to-noise ratio (SNR) of the system. Then, we derive an approximate closed-form expression of the average packet error probability (APEP). Additionally, we optimize the channel uses in the WET and WIT phases to maximize the effective throughput (ET) of the system. Finally, the effectiveness of the proposed solution is verified by Monte-Carlo simulation.",

keywords = "Average packet error probability, Effective throughput, Short-packet communications, uRLLC, Wireless energy transfer",

author = "Bingxin Zhang and Kezhi Wang and Kun Yang and Guopeng Zhang",

note = "Funding Information: This work was supported by the National Natural Science Foundation of China under Grant 61620106011, Grant U1705263, Grant 61871076, and Grant 61971421.",

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AU - Zhang, Bingxin

AU - Wang, Kezhi

AU - Yang, Kun

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N1 - Funding Information: This work was supported by the National Natural Science Foundation of China under Grant 61620106011, Grant U1705263, Grant 61871076, and Grant 61971421.

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Y1 - 2022/2/1

N2 - In this letter, we analyse and optimize an intelligent reflecting surface (IRS)-assisted ultra-reliable and low-latency communications (uRLLC) system supported by wireless energy transfer (WET) technology, in which short packets are used in both the WET and wireless information transfer (WIT) phases. We first present the statistical features of the signal-to-noise ratio (SNR) of the system. Then, we derive an approximate closed-form expression of the average packet error probability (APEP). Additionally, we optimize the channel uses in the WET and WIT phases to maximize the effective throughput (ET) of the system. Finally, the effectiveness of the proposed solution is verified by Monte-Carlo simulation.

AB - In this letter, we analyse and optimize an intelligent reflecting surface (IRS)-assisted ultra-reliable and low-latency communications (uRLLC) system supported by wireless energy transfer (WET) technology, in which short packets are used in both the WET and wireless information transfer (WIT) phases. We first present the statistical features of the signal-to-noise ratio (SNR) of the system. Then, we derive an approximate closed-form expression of the average packet error probability (APEP). Additionally, we optimize the channel uses in the WET and WIT phases to maximize the effective throughput (ET) of the system. Finally, the effectiveness of the proposed solution is verified by Monte-Carlo simulation.

KW - Average packet error probability

KW - Effective throughput

KW - Short-packet communications

KW - uRLLC

KW - Wireless energy transfer

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DO - 10.1109/LWC.2021.3126596

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JO - IEEE Wireless Communications Letters

JF - IEEE Wireless Communications Letters

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IRS-Assisted Short Packet Wireless Energy Transfer and Communications

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Keywords

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