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http://dx.doi.org/10.4218/etrij.2021-0013

Efficient power allocation algorithm in downlink cognitive radio networks  

Abdulghafoor, Omar (Electronic & Telecommunications Department, College of Engineering, The American University of Kurdistan)
Shaat, Musbah (CTTC)
Shayea, Ibraheem (Faculty of Electrical and Electronics Engineering, Istanbul Technical University)
Mahmood, Farhad E. (Electrical Engineering Department, College of Engineering, University of Mosul)
Nordin, Rosdiadee (EES Department, Faculty of Engineering and Built Environment, The National University of Malaysia)
Lwas, Ali Khadim (R&D, Ministry of Industry and Minerals)
Publication Information
ETRI Journal / v.44, no.3, 2022 , pp. 400-412 More about this Journal
Abstract
In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).
Keywords
cognitive radio; OFDM; pricing technique; resource allocation;
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Times Cited By KSCI : 4  (Citation Analysis)
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