Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/31516
Title: Performance Analysis of IRS-Assisted Multi-Cell Data and Energy Integrated Networks
Authors: Zhang, B
Yang, K
Wang, K
Zhang, G
Keywords: intelligent reflecting surface (IRS);data and energy integrated network (DEIN);wireless energy transfer (WET);multi-cell;performance analysis
Issue Date: 15-May-2025
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Zhang, B. et al. (2025) 'Performance Analysis of IRS-Assisted Multi-Cell Data and Energy Integrated Networks', IEEE Transactions on Wireless Communications, 0 (early access), pp. 1 - 13. doi: 10.1109/TWC.2025.3568198.
Abstract: Intelligent reflecting surface (IRS) can significantly enhance the performance of data and energy integrated networks (DEIN) by adjusting its amplitude and/or phase. However, there is a lack of comprehensive performance analysis model for realistic DEIN where multiple cells exist rather than only one cell as assumed by most existing work. In this paper, we consider an IRS-assisted multi-cell DEIN. Specifically, in the downlink wireless energy transfer (WET) stage, the hybrid access point (HAP) in each cell broadcasts radio frequency (RF) energy signals to edge user equipments (UEs). Subsequently, during the uplink wireless information transfer (WIT) stage, the edge UEs employ the harvested energy to send their information to the HAP. We first represent the statistical characteristics of the signal-to-interference-plus-noise ratio (SINR) at the edge UE. Then, we derive the closed-form expressions for outage probability, ergodic rate and average symbol error probability of the edge UE in the typical cell. To gain more insights, we obtain the minimum required number of reflection elements and a sub-optimal solution for time allocation coefficients. Finally, extensive numerical results are provided to validate the correctness of the theoretical results.
URI: https://bura.brunel.ac.uk/handle/2438/31516
DOI: https://doi.org/10.1109/TWC.2025.3568198
ISSN: 1536-1276
Other Identifiers: ORCiD: Kun Yang https://orcid.org/0000-0002-6782-6689
ORCiD: Kezhi Wang https://orcid.org/0000-0001-8602-0800
ORCiD: Guopeng Zhang https://orcid.org/0000-0001-7524-3144
Appears in Collections:Dept of Computer Science Research Papers

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