Weighted Sum Power Minimization for Cooperative Spectrum Sharing in Cognitive Radio Networks

This letter introduces weighted sum power (WSP), a new performance metric for wireless resource allocation during cooperative spectrum sharing in cognitive radio networks, where the primary and secondary nodes have different priorities and quality of service (QoS) requirements. Compared to using energy efficiency (EE) and weighted sum energy efficiency (WSEE) as performance metrics and optimization objectives of wireless resource allocation towards green communication, the linear character of WSP can reduce the complexity of optimization problems. Meanwhile, the weights assigned to different nodes are beneficial for managing their power budget. Using WSP as the optimization objective, a suboptimal resource allocation scheme is proposed, leveraging linear programming and Newton’s method. Simulations verify that the proposed scheme provides near-optimal performance with low computation time. Furthermore, the initial approximate value selection in Newton’s method is also optimized to accelerate the proposed scheme.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-11-22
DOI
https://doi.org/10.1109/lcomm.2024.3504957
Citations
6
Primary Topic
Cognitive Radio Networks and Spectrum Sensing
Type
article
Field-Weighted Citation Impact
2.09
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article

Weighted Sum Power Minimization for Cooperative Spectrum Sharing in Cognitive Radio Networks

Yang Yu, Xiaoqing Tang
6 citations
IEEE Communications Letters
Cognitive Radio Networks and Spectrum Sensing
2.09
article

Weighted Sum Power Minimization for Cooperative Spectrum Sharing in Cognitive Radio Networks

Yang Yu, Xiaoqing Tang
article en
6 citations

Abstract

This letter introduces weighted sum power (WSP), a new performance metric for wireless resource allocation during cooperative spectrum sharing in cognitive radio networks, where the primary and secondary nodes have different priorities and quality of service (QoS) requirements. Compared to using energy efficiency (EE) and weighted sum energy efficiency (WSEE) as performance metrics and optimization objectives of wireless resource allocation towards green communication, the linear character of WSP can reduce the complexity of optimization problems. Meanwhile, the weights assigned to different nodes are beneficial for managing their power budget. Using WSP as the optimization objective, a suboptimal resource allocation scheme is proposed, leveraging linear programming and Newton’s method. Simulations verify that the proposed scheme provides near-optimal performance with low computation time. Furthermore, the initial approximate value selection in Newton’s method is also optimized to accelerate the proposed scheme.

IEEE Communications LettersVol. 29(1)
China Three Gorges University (CN), Hubei University (CN)
Openalex Percentile: Top 12%
Cognitive Radio Networks and Spectrum Sensing
2.09
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Weighted Sum Power Minimization for Cooperative Spectrum Sharing in Cognitive Radio Networks — Yang Yu, Xiaoqing Tang · IEEE Communications Letters (2024) | TGRS Research Map | TGRS