A Cross-Layer Based Location-Aware Forwarding Using Distributed TDMA MAC for Ad-Hoc Cognitive Radio Networks

Yarnagula, Hema Kumar; Deka, Sanjib Kumar; Sarma, Nityananda

doi:10.1007/s11277-017-4098-2

Cited by 6 publications

(1 citation statement)

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“…A multi‐objective optimization problem (MOP) was formulated in this system for maximizing the ergodic sum rate and reducing the interference at the receiver side. Yarnagula et al developed a crosslayer‐based location aware forwarding protocol for avoiding the network collisions with better bandwidth utilization. Here, the channel selection strategy was used to select the optimized channel for increasing the reliability of data packets.…”

Section: Related Workmentioning

confidence: 99%

IDsMA: An integrated digital signature and mutual authentication mechanism for securing the cognitive radio networks

Balamurugan

Kumar

2019

Int J Communication

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Summary Enabling a reliable and secure communication in cognitive radio networks (CRNs) is one of the interesting and demanding research areas and these days, it is used in wide range of applications. The traditional works mainly aimed to improve the spectrum efficiency and bandwidth utilization of the CRN. Moreover, it focused on attack detection in the network for improving the reliability. Thus, this work intended to secure the CRN by considering the objectives of both attack detection and quality of service (QoS) improvement. For this purpose, an integrated digital signature and mutual authentication (IDsMA) mechanism is proposed in this paper, which incorporates the benefits of both security and reliability. Also, the Rivest‐Sharmir‐Adlemann (RSA) algorithm is utilized to encrypt and decrypt the data at the transmitter and receiver side. Here, the unique user ID is generated by the service eNodeB based on the hash function, which is validated at the server side for validating the authenticity of the user. Furthermore, the particle swarm optimization (PSO) and relevant vector machine (RVM) techniques are utilized for optimal channel selection and attack classification. The simulation results evaluate the performance of the proposed technique by using various performance measures. Also, its superiority is proved by comparing the proposed technique with the existing techniques.

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Section: Related Workmentioning

confidence: 99%