Optimization of Resource Allocation for Heterogeneous Services in OFDM Based Cognitive Radio Networks Using Artificial Bee Colony

Salman, Ayesha; Qureshi, Ijaz Mansoor; Saleem, Shahryar; Saeed, Sarah O. M.

doi:10.1109/raee.2019.8886951

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…( 2), the total/maximum power on the i th subcarrier for the m th cognitive user is modeled as in Eq. (10).…”

Section: Subcarrier Allocation Algorithmmentioning

confidence: 99%

“…In CRNs, the problematic of resource allocation (RA) is important and has managed in many researches [3][4][5][6][7]. Moreover, the orthogonal frequency-division multiplexing (OFDM) multicarrier technique is considered a promising method for cognitive radio networks (CRNs) due to its consistency and flexibility in managing resources to CR users [8][9][10]. In the OFDM network, both CR and PU exist close to each other, which results in common interference, which is a preventive factor affecting the performance of both CRNs and PUNs [11].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

Abdulghafoor¹,

Shaat²,

Shayea³

et al. 2023

Computers, Materials &Amp; Continua

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The computational complexity of resource allocation processes, in cognitive radio networks (CRNs), is a major issue to be managed. Furthermore, the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users, CRs, and primary users, PUs, exist in the identical geographical area. Hence, this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarios while limiting interference to PUs to allowable threshold. Hence, this paper, compared to other frameworks proposed in the literature, proposes a two-step approach to reduce the complexity of the proposed mathematical model. In the first step, the subcarriers are assigned to the users of the CRN, while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second stage. The main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks, which has been achieved by including a pricing function in the proposed cost function. Finally, the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing (OFDM). Simulation results prove that the performance of the proposed algorithm is better than other algorithms, albeit with a lesser complexity of O(NM) + O(Nlog(N)).

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“…( 2), the total/maximum power on the i th subcarrier for the m th cognitive user is modeled as in Eq. (10).…”

Section: Subcarrier Allocation Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

Abdulghafoor¹,

Shaat²,

Shayea³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…A number of the problems have been solved by ABC in different areas these include Communication [45][46][47], TSP [48,49], Power Engineering [50,51], Health care [52][53][54], Management [55,56], Image processing [57,58], and many other applications.…”

Section: Stage Vmentioning

confidence: 99%

A survey of the state-of-the-art swarm intelligence techniques and their application to an inverse design problem

Khan

Ling

2020

J Comput Electron

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This paper encompasses a detailed review of state-of-the-art swarm-based algorithms with a focus on their applications along with a discussion on the merits and limitations of each algorithm. Further, a recently developed Advanced Particle Swarm Optimization (APSO) algorithm was compared with the different state-of-the-art-swarmbased algorithms through solving an electromagnetic inverse problem. Results showed that the APSO algorithm has outperformed the other algorithms. This research provides a scientific guideline for the comparison of different swarmbased algorithms and their utilization regarding specific applications.

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Analysis of system outage probability in underlay cognitive two-way amplify-and-forward relay networks

Al‐Zubi

Issa

Zghoul

et al. 2020

Computer Communications

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Optimization of Resource Allocation for Heterogeneous Services in OFDM Based Cognitive Radio Networks Using Artificial Bee Colony

Cited by 3 publications

References 14 publications

Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

A survey of the state-of-the-art swarm intelligence techniques and their application to an inverse design problem

Analysis of system outage probability in underlay cognitive two-way amplify-and-forward relay networks

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