Intelligent Reflecting Surface Assisted Multi-User Robust Secret Key Generation for Low-Entropy Environments.

Yuwei Gao, Dengke Guo, Jun Xiong, Dongtang Ma

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications.Entropy (Basel, Switzerland) · 2022
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yuwei GaoCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410072, China.ORCID 0000-0001-7523-5662

Dengke GuoCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410072, China.

Jun XiongCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410072, China.ORCID 0000-0002-2642-5512

Dongtang MaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410072, China.

Funding

Haitao Zhao 61931020

6 · The paper itself

Abstract

Channel secret key generation (CSKG), assisted by the new material intelligent reflecting surface (IRS), has become a new research hotspot recently. In this paper, the key extraction method in the IRS-aided low-entropy communication scenario with adjacent multi-users is investigated. Aiming at the problem of low key generation efficiency due to the high similarity of channels between users, we propose a joint user allocation and IRS reflection parameter adjustment scheme, while the reliability of information exchange during the key generation process is also considered. Specifically, the relevant key capability expressions of the IRS-aided communication system is analyzed. Then, we study how to adjust the IRS reflection matrix and allocate the corresponding users to minimize the similarity of different channels and ensure the robustness of key generation. The simulation results show that the proposed scheme can bring higher gains to the performance of key generation.

Indexed as

key generationmulti-userphysical layer security

Identifiers

PMID34682066

DOI10.3390/e23101342

PMCPMC8535129

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.