A novel relay selection algorithm using ant colony optimization with artificial noise for secrecy enhancement in cooperative networks

M, Shemi P; Jibukumar, M G; Sabu, M. K.

doi:10.1002/dac.3739

Cited by 9 publications

(3 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relay communication has been generally used in the cellular network, UAV communication, and other fields, which can effectively improve the quality of communication 10‐12 . A new relay selection percept together with artificial noise was proposed to improve the privacy of cooperative networks, in the presence of a malicious eavesdropper 13 . In Reference 14, based on matching game theory, a new distributed relay allocation method is proposed to optimize system throughput.…”

Section: Related Workmentioning

confidence: 99%

Joint relay and channel selection in relay‐aided anti‐jamming system: A reinforcement learning approach

Huang

Xu²,

Chen

et al. 2021

Trans Emerging Tel Tech

View full text Add to dashboard Cite

In this article, a joint relay and channel selection problem is investigated in multi‐relay anti‐jamming communication system. Considering the jamming pattern and the relay node (RN) location distribution are unknown, the relay and channel selection problem is formulated as Markov decision processes (MDPs). Different from the existing research on anti‐jamming communication, in this article, the source node (SN) and all RNs are considered as agents who collaboratively learn the environment and make anti‐jamming decisions. A reinforcement‐learning‐based joint relay and channel selection method is proposed to achieve relay‐aided anti‐jamming communication. Specifically, the SN tries to make the optimal selection of relay which is under the least jamming threat, while the RN will access the jamming‐free channels. Various simulation results show that the algorithm can quickly learn the unknown changing pattern of the jamming environment, and make the effective joint relay and channel decisions to obtain high communication throughput which is close to the optimal.

show abstract

Section: Related Workmentioning

confidence: 99%

Joint relay and channel selection in relay‐aided anti‐jamming system: A reinforcement learning approach

Huang

Xu²,

Chen

et al. 2021

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…Optimization solvers are mostly hard in computation that suffer from scalability problems, whereas the running time of stable matching schemes is polynomial. To decrease the complexity of computational, most of the works assume a subset of the joint optimization problems [7][8][9][10][11]. Because the relay selection and channel assignment are naturally combinatorial, matching-based approaches are adopted in some articles [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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

Amini

Abouei

2022

IET Communications

View full text Add to dashboard Cite

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.

show abstract

“…The advantage of this method is simple operation, but after many iterations it will cause lack of particle diversity. If we use ant colony optimization to make particles with smaller weight move to the optimal position, and keep the position of particles with larger weight unchanged, the particles will have better distribution and keep the diversity of particles [21].…”

Section: Introductionmentioning

confidence: 99%

A Novel Cooperative Localization Method Based on IMU and UWB

Han

Wei

et al. 2020

Sensors

View full text Add to dashboard Cite

In this paper, a range-based cooperative localization method is proposed for multiple platforms of various structures. The localization system of an independent platform might degrade or fail due to various reasons such as GPS signal-loss, inertial measurement unit (IMU) accumulative errors, or emergency reboot. It is a promising approach to solve this problem by using information from neighboring platforms, thus forming a cooperative localization network that can improve the navigational robustness of each platform. Typical ranging-based ultra-wideband (UWB) cooperative localization systems require at least three auxiliary nodes to estimate the pose of the target node, which is often hard to meet especially in outdoor environment. In this work, we propose a novel IMU/UWB-based cooperative localization solution, which requires a minimum number of auxiliary nodes that is down to 1. An Adaptive Ant Colony Optimization Particle Filter (AACOPF) algorithm is customized to integrate the dead reckoning (DR) system and auxiliary nodes information with no prior information required, resulting in accurate pose estimation, while to our knowledge the azimuth have not been estimated in cooperative localization for the insufficient observation of the system. We have given the condition when azimuth and localization are solvable by analysis and by experiment. The feasibility of the proposed approach is evaluated through two filed experiments: car-to-trolley and car-to-pedestrian cooperative localization. The comparison results also demonstrate that ACOPF-based integration is better than other filter-based methods such as Extended Kalman Filter (EKF) and traditional Particle Filter (PF).

show abstract

A novel relay selection algorithm using ant colony optimization with artificial noise for secrecy enhancement in cooperative networks

Cited by 9 publications

References 34 publications

Joint relay and channel selection in relay‐aided anti‐jamming system: A reinforcement learning approach

Joint relay and channel selection in relay‐aided anti‐jamming system: A reinforcement learning approach

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

A Novel Cooperative Localization Method Based on IMU and UWB

Contact Info

Product

Resources

About