2021
DOI: 10.1109/tifs.2021.3103062
|View full text |Cite
|
Sign up to set email alerts
|

Multi-Agent Reinforcement Learning-Based Buffer-Aided Relay Selection in IRS-Assisted Secure Cooperative Networks

Abstract: This paper proposes a multi-agent deep reinforcement learning-based buffer-aided relay selection scheme for an intelligent reflecting surface (IRS)-assisted secure cooperative network in the presence of an eavesdropper. We consider a practical phase model where both phase shift and reflection amplitude are discrete variables to vary the reflection coefficients of the IRS. Furthermore, we introduce the buffer-aided relay to enhance the secrecy performance, but the use of the buffer leads to the cost of delay. T… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
31
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 60 publications
(31 citation statements)
references
References 47 publications
(62 reference statements)
0
31
0
Order By: Relevance
“…As shown in Fig. 1, Case I refers to the scenario where the RIS-destination link is ignored in the first time slot, which has been assumed in most existing works (see, e.g., [25]- [32]). The channel between source and relay at subcarrier p = 1, 2 .…”
Section: A Case-i: No Ris-destination Link In Time Slot Onementioning
confidence: 99%
See 2 more Smart Citations
“…As shown in Fig. 1, Case I refers to the scenario where the RIS-destination link is ignored in the first time slot, which has been assumed in most existing works (see, e.g., [25]- [32]). The channel between source and relay at subcarrier p = 1, 2 .…”
Section: A Case-i: No Ris-destination Link In Time Slot Onementioning
confidence: 99%
“…To further improve the communication performance in relaying/RIS networks, the recent works in [25]- [32] have been investigating the intergation of RIS and relay in wireless networks, rather than unilaterally considering one of them. To be specific, a RIS-assisted relaying system was studied in [25], where tight upper bounds on the ergodic capacity were obtained under different channel environments.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Motivated by this, Huang et al, [71] proposed a multi-agent deep reinforcement learning-based buffer-aided relay selection scheme for an IRS-assisted secure cooperative network in the presence of an eavesdropper. They considered a practical scenario where both phase shift and reflection amplitude of the IRSs are optimized to improve the wireless network's performance.…”
Section: B Reinforcement Learning Techniques For Irs-deployment For T...mentioning
confidence: 99%
“…Simulation results showed that the proposed learning-based scheme used an iterative approach to learn from the environment to approximate an optimal solution by exploring multiple agents, which outperforms benchmark schemes. However, this paper [71] only considered a single untrusted relay as an eavesdropper in the proposed network. This can be further extended to consider multiple eavesdropper scenarios.…”
Section: B Reinforcement Learning Techniques For Irs-deployment For T...mentioning
confidence: 99%