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

Gao, Yuwei; Guo, Dengke; Xiong, Jun; Ma, Dongtang

doi:10.3390/e23101342

Cited by 5 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [23], channel key extraction in a static multi-user down link scenario is considered. It is observed that due to the high channel similarity between users, the problem of low-key generation arises.…”

Section: Related Workmentioning

confidence: 99%

Improved Rate of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces for Vehicular Networks

et al. 2022

View full text Add to dashboard Cite

The reconfigurable intelligent surfaces (RIS) is a new technology that can be utilized to provide security to vehicle-to-vehicle (V2V) communications at the physical layer. In this paper, we achieve a higher key generation rate for V2V communications at lower cost and computational complexity. We investigate the use of a passive RIS as a relay, to introduce channel diversity and increase the key generation rate (KGR), accordingly. In this regard, we consider the subsets of consecutive reflecting elements instead of the RIS as a whole in a time slot, i.e., instead of a single reflector, the subsets of reflectors are utilized to redirect the signal to the receiver via passive beam forming. Simulations are conducted for different sizes of RISs and subsets of reflectors per RIS. From the results obtained, it can be seen that when we consider a subset of reflectors instead of the RIS as a single entity, it becomes increasingly difficult to intercept the signal at the eavesdropper. In the proposed scheme, the KGR reaches up to 6 bps per time slot.

show abstract

Section: Related Workmentioning

confidence: 99%

Improved Rate of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces for Vehicular Networks

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Considered promising technology, intelligent reflecting surfaces (IRSs) have recently received substantial attention [12][13][14][15][16]. IRS consists of a large number of passive elements which can introduce controllable phase shifts.…”

Section: Introductionmentioning

confidence: 99%

Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications

Cao

Zhu

Feng

et al. 2022

Entropy

View full text Add to dashboard Cite

Satellite communication is expected to play a vital role in realizing Internet of Remote Things (IoRT) applications. This article considers an intelligent reflecting surface (IRS)-assisted downlink low Earth orbit (LEO) satellite communication network, where IRS provides additional reflective links to enhance the intended signal power. We aim to maximize the sum-rate of all the terrestrial users by jointly optimizing the satellite’s precoding matrix and IRS’s phase shifts. However, it is difficult to directly acquire the instantaneous channel state information (CSI) and optimal phase shifts of IRS due to the high mobility of LEO and the passive nature of reflective elements. Moreover, most conventional solution algorithms suffer from high computational complexity and are not applicable to these dynamic scenarios. A robust beamforming design based on graph attention networks (RBF-GAT) is proposed to establish a direct mapping from the received pilots and dynamic network topology to the satellite and IRS’s beamforming, which is trained offline using the unsupervised learning approach. The simulation results corroborate that the proposed RBF-GAT approach can achieve more than 95% of the performance provided by the upper bound with low complexity.

show abstract

“…They present their results using two metrics which are SKR and key mismatch rate (KMR). The authors in [8] propose a joint user allocation scheme and an RIS reflection parameter adjustment scheme to enhance key generation efficiency in a multi-user communication scenario. They compare the result against a scheme without an RIS and find that the RIS indeed boosts performance by reducing channel similarities between adjacent users and thus the enhancing efficiency of key generation.…”

Section: Introductionmentioning

confidence: 99%

Channel Estimation for Distributed Intelligent Reflecting Surfaces Assisted Multi-User MISO Systems

Alwazani

Nadeem

Chaaban

2020

2020 IEEE Globecom Workshops (GC WKSHPS

View full text Add to dashboard Cite

Intelligent reflecting surfaces (IRSs)-assisted wireless communication promises improved system performance, while posing new challenges in channel estimation (CE) due to the passive nature of the reflecting elements. Although a few CE protocols for IRS-assisted multiple-input single-output (MISO) systems have appeared, they either require long channel training times or are developed under channel sparsity assumptions. Moreover, existing works focus on a single IRS, whereas in practice multiple such surfaces should be installed to truly benefit from the concept of reconfiguring propagation environments. In light of these challenges, this paper tackles the CE problem for the distributed IRSs-assisted multi-user MISO system. An optimal CE protocol requiring relatively low training overhead is developed using Bayesian techniques under the practical assumption that the BS-IRSs channels are dominated by the line-of-sight (LoS) components. An optimal solution for the phase shifts vectors required at all IRSs during CE is determined and the minimum mean square error (MMSE) estimates of the BSusers direct channels and the IRSs-users channels are derived. Simulation results corroborate the normalized MSE (NMSE) analysis and establish the advantage of the proposed protocol as compared to benchmark scheme in terms of training overhead.

show abstract

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

Cited by 5 publications

References 23 publications

Improved Rate of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces for Vehicular Networks

Improved Rate of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces for Vehicular Networks

Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications

Channel Estimation for Distributed Intelligent Reflecting Surfaces Assisted Multi-User MISO Systems

Contact Info

Product

Resources

About