Intelligent Physical Layer Secure Relay Selection for Wireless Cooperative Networks with Multiple Eavesdroppers

Kamboj, Anil Kumar; Jindal, Poonam; Verma, Pankaj

doi:10.1007/s11277-021-08458-4

Cited by 13 publications

(4 citation statements)

References 38 publications

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“…Toan et al [13] studied the end-to-end performance of multi-hop wireless-powered relaying networks cognitively operating with primary networks over Nakagami-m fading channels. In [14], A. K. Kamboj et al developed the machine learning algorithms for relay selection to improve the physical layer security of a dual-hop non-regenerative wireless cooperative network. However, to the best of authors knowledge, the aforementioned works did not develop an analytical mathematical model to ensure the security in multicasting considering the diversity order provided by the multi-hop relaying technique.…”

Section: Related Workmentioning

confidence: 99%

Secure Wireless Multicasting through Nakagami-m Fading Channels with Multi-Hop Relaying

Rahman¹,

Sarkar²,

Hasan³

2023

JCC

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The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closedform analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting.

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Section: Related Workmentioning

confidence: 99%

Secure Wireless Multicasting through Nakagami-m Fading Channels with Multi-Hop Relaying

Rahman¹,

Sarkar²,

Hasan³

2023

JCC

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“…For example, by combining PLS, RS, and ML, the authors of [32] transformed the RS problem into a multi-class classification problem. Moreover, the analysis in [33] transformed the RS approaches into a prediction and decision-making problem. However, it must be noted that the availability of a large amount of historical data for training the ML algorithm is challenging, especially in rapidly changing fading environments.…”

Section: A Related Workmentioning

confidence: 99%

Secure Relay Selection with Outdated CSI in Cooperative Wireless Vehicular Networks: A DQN Approach

Ghourab¹,

Bariah²,

Muhaidat³

et al. 2022

Preprint

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Cooperative communications is a core research area in wireless vehicular networks (WVNs), thanks to its capability to mitigate fading and improve spectral efficiency. In a cooperative scenario, the performance of the system is improved by selecting the best relay for data transmission among a group of available relays. However, due to the mobility of WVNs, the best relay is often selected in practice based on outdated channel state information (CSI), which in turn affects the overall system performance. Therefore, there is a need for a robust relay selection scheme (RSS) that improves the overall achievable performance of an outdated CSI. Motivated by this and considering the advantageous features of autoregressive moving average (ARMA), in the present work we model a cooperative vehicular communication scenario with relay selection as a Markov decision process (MDP) and propose two deep Q-networks (DQNs), namely DQN-RSS and DQN-RSS-ARMA. In the proposed framework, two deep reinforcement learning (RL)-based RSS are trained based on the intercept probability, aiming to select the optimal vehicular relay from a set of multiple relays. We then compare the proposed RSS with the conventional methods and evaluate the performance of the network from the security point of view. Simulation results show that DQN-RSS and DQN-RSS-ARMA perform better than conventional approaches, and they reduce intercept probability by approximately 15\% and 30\%, respectively, compared to the ARMA approach.

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“…In wireless communications, choosing the best relay has been introduced for utilizing path diversity benefits [17]. Studies on cooperative communications could be broadly classified into the three categories: i) physical layer algorithms that exploit distributed antennas on other nodes in the network resulted in several cooperative protocols at the physical layer [18][19][20][21][22], ii) network layer algorithms for cooperative networks, where the literature in this field formulate challenges as nonlinear program in which provided solutions are appropriate only for a few simple network structures. For this category, different relay selection techniques have been proposed in recent studies [16,[23][24][25][26].…”

Section: Related Workmentioning

confidence: 99%

A matching‐based context‐aware relay assignment scheme with power control in ad‐hoc wireless networks

Amini

Abouei

2022

IET Communications

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In this paper, an emergency ad‐hoc network based on cognitive radio is considered. It is assumed that secondary users (SUs) are moving agents in which some fixed agents namely distributed relays (DRs), forward the data gathered by SUs to destination. The main goal is to maximize the capacity of data gathering in destination with respect to the maximum interference tolerable by primary users (PU), and SU's and DR's power constraints. A mixed‐integer nonlinear model (MINLP) for joint relay assignment and power allocation is shown. Given that MINLP problems are NP‐Hard, a two interdependent solutions are proposed to achieve the relay assignment and power control. A social‐aware dynamic relay assignment algorithm (SADRA) based on many‐to‐one matching is proposed. In this matching, the preference list of DRs is the result of mean opinion scores ranking that two roulette wheel selection and random walk selection techniques are applied to eliminate the same priorities. In the second phase, a greedy adaptive algorithm for non‐convex power allocation problem that converges to the component‐wise minimal power is proposed. It is shown that the SADRA algorithm converges to a two‐sided exchange stable matching. The superior performance of the proposed SADRA algorithm is verified by the simulation results.

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Intelligent Physical Layer Secure Relay Selection for Wireless Cooperative Networks with Multiple Eavesdroppers

Cited by 13 publications

References 38 publications

Secure Wireless Multicasting through Nakagami-<i>m</i> Fading Channels with Multi-Hop Relaying

Secure Wireless Multicasting through Nakagami-<i>m</i> Fading Channels with Multi-Hop Relaying

Secure Relay Selection with Outdated CSI in Cooperative Wireless Vehicular Networks: A DQN Approach

A matching‐based context‐aware relay assignment scheme with power control in ad‐hoc wireless networks

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Intelligent Physical Layer Secure Relay Selection for Wireless Cooperative Networks with Multiple Eavesdroppers

Cited by 13 publications

References 38 publications

Secure Wireless Multicasting through Nakagami-&lt;i&gt;m&lt;/i&gt; Fading Channels with Multi-Hop Relaying

Secure Wireless Multicasting through Nakagami-&lt;i&gt;m&lt;/i&gt; Fading Channels with Multi-Hop Relaying

Secure Relay Selection with Outdated CSI in Cooperative Wireless Vehicular Networks: A DQN Approach

A matching‐based context‐aware relay assignment scheme with power control in ad‐hoc wireless networks

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Secure Wireless Multicasting through Nakagami-<i>m</i> Fading Channels with Multi-Hop Relaying

Secure Wireless Multicasting through Nakagami-<i>m</i> Fading Channels with Multi-Hop Relaying