PSO-based Resource Allocation Scheme in Cognitive Radio Network

Increasing demand for spectrum causes the emergence of technologies like Cognitive Radio (CR). The resources like bandwidth and energy are primarily shared by the primary and secondary users in the CR network. The utilization of resources is dependent on the number of nodes, topology dimension, packet generation rate, and time of utilization of the channel. Therefore, the optimization of resources in CR is a need of the hour. In the presented paper, a PSO-based resource allocation scheme is implemented. The input parameters like the number of secondary user nodes, packet generation rate, dimension of the network, and simulation time are targeted to get optimum results of packet delivery ratio, average throughput, average delay, and energy consumption. To implement CR, NS-2 is used. The fitness equations are obtained by varying the input parameters in a given range. Curve-fitting software is used to get fitness equations. These fitness equations are then used in the PSO algorithm, which is implemented in MATLAB. With the implementation of a PSO-based resource allocation scheme, the performance of packet delivery ratio, throughput, delay, and energy consumption increased by 11.76%, 22.85%, 80.6%, and 76.58%, respectively.

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Published
2024-10-04
DOI
https://doi.org/10.1109/mac61551.2024.10837129
Primary Topic
Cognitive Radio Networks and Spectrum Sensing
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article
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PSO-based Resource Allocation Scheme in Cognitive Radio Network

Vivek Rajpoot, T. Bhavani, Manuvarthi Mounisha, Veluvali Krishna Vamsi et al.
Cognitive Radio Networks and Spectrum Sensing
article

PSO-based Resource Allocation Scheme in Cognitive Radio Network

Vivek Rajpoot, T. Bhavani, Manuvarthi Mounisha, Veluvali Krishna Vamsi, Hemachandra Karlapudi, Naga Vamsi Krishna Bandi
article en

Abstract

Increasing demand for spectrum causes the emergence of technologies like Cognitive Radio (CR). The resources like bandwidth and energy are primarily shared by the primary and secondary users in the CR network. The utilization of resources is dependent on the number of nodes, topology dimension, packet generation rate, and time of utilization of the channel. Therefore, the optimization of resources in CR is a need of the hour. In the presented paper, a PSO-based resource allocation scheme is implemented. The input parameters like the number of secondary user nodes, packet generation rate, dimension of the network, and simulation time are targeted to get optimum results of packet delivery ratio, average throughput, average delay, and energy consumption. To implement CR, NS-2 is used. The fitness equations are obtained by varying the input parameters in a given range. Curve-fitting software is used to get fitness equations. These fitness equations are then used in the PSO algorithm, which is implemented in MATLAB. With the implementation of a PSO-based resource allocation scheme, the performance of packet delivery ratio, throughput, delay, and energy consumption increased by 11.76%, 22.85%, 80.6%, and 76.58%, respectively.

Vellore Institute of Technology University (IN)
Openalex Percentile: Top 70%
Cognitive Radio Networks and Spectrum Sensing
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