eprintid: 10185517
rev_number: 7
eprint_status: archive
userid: 699
dir: disk0/10/18/55/17
datestamp: 2024-01-16 13:19:07
lastmod: 2024-01-16 13:19:07
status_changed: 2024-01-16 13:19:07
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Shahiri, Vahid
creators_name: Behroozi, Hamid
creators_name: Kuhestani, Ali
creators_name: Wong, Kai-Kit
title: Reconfigurable Intelligent Surface-Assisted Secret Key Generation Under Spatially Correlated Channels in Quasi-Static Environments
ispublished: inpress
divisions: UCL
divisions: B04
divisions: C05
divisions: F46
keywords: Physical layer secret key generation, spatial
correlation, reconfigurable intelligent surface (RIS), achievable key generation rate
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Physical layer key generation (PLKG) can significantly enhance the security of classic encryption schemes by efficiently providing secret keys in resource-limited network like the Internet of Things (IoT). However, reaching a high key generation rate (KGR) is challenging in applications like smart home or remote area sensing with quasi-static channels. Recently, exploiting reconfigurable intelligent surface (RIS) to induce randomness in quasi-static wireless channels has received significant research interest. However, the inherent spatial correlation among the RIS elements is rarely studied, which can alter the optimum PLKG approach in terms of KGR and randomness in the key sequence. Specifically, for the first time, in this contribution, we take into account a spatially correlated RIS, which intends to enhance the KGR in a quasi-static medium. Novel closed-form analytical expressions for KGR are derived for the two cases of random phase shift (RPS) and our proposed equal phase shift (EPS) in the RIS elements. We also analyze the correlation between the channel samples to ensure the randomness of the generated secret key sequence. It is shown that the EPS scheme can effectively exploit the inherent spatial correlation between the RIS elements and it leads to a higher KGR compared to the widely used RPS strategy. We further formulate an optimization problem in which we determine the optimal portion of time dedicated to direct and indirect channel estimation, which has never been addressed in the previous studies. We show the accuracy and the fast convergence of our sequential convex programming (SCP) based algorithm and discuss the various parameters affecting spatially correlated RIS-assisted PLKG.
date: 2024-01-02
date_type: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
official_url: http://dx.doi.org/10.1109/jiot.2023.3349354
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2139783
doi: 10.1109/JIOT.2023.3349354
lyricists_name: Wong, Kai-Kit
lyricists_id: KWONG98
actors_name: Wong, Kai-Kit
actors_id: KWONG98
actors_role: owner
full_text_status: public
publication: IEEE Internet of Things Journal
pagerange: 1-1
issn: 2327-4662
citation:        Shahiri, Vahid;    Behroozi, Hamid;    Kuhestani, Ali;    Wong, Kai-Kit;      (2024)    Reconfigurable Intelligent Surface-Assisted Secret Key Generation Under Spatially Correlated Channels in Quasi-Static Environments.                   IEEE Internet of Things Journal     p. 1.    10.1109/JIOT.2023.3349354 <https://doi.org/10.1109/JIOT.2023.3349354>.    (In press).    Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10185517/1/SKG_Spatially_Correlated_IRS.pdf