Max-Min Energy-Efficient Optimization for Cognitive Heterogeneous Networks With Spectrum Sensing Errors and Channel Uncertainties

In this letter, we design a robust resource allocation algorithm for a non-orthogonal multiple access (NOMA)-based cognitive heterogeneous network under spectrum sensing errors and channel uncertainties. Our objective is to maximize the minimum energy efficiency of femtocells subject to the maximum...

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Published inIEEE wireless communications letters Vol. 11; no. 6; pp. 1113 - 1117
Main Authors Xu, Yongjun, Yang, Meng, Yang, Yang, Ye, Yinghui, Hu, Rose Qingyang, Li, Dong
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.06.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Cellular communication
channel uncertainties
Cognitive heterogeneous networks
Computational geometry
Convexity
energy efficiency
Errors
Femtocells
Heterogeneous networks
Interference
Maximum power
NOMA
Nonorthogonal multiple access
Optimization
Resource allocation
Resource management
Robustness (mathematics)
Sensors
spectrum sensing errors
Uncertainty
Online AccessGet full text
ISSN2162-2337
2162-2345
DOI10.1109/LWC.2021.3130632

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Abstract In this letter, we design a robust resource allocation algorithm for a non-orthogonal multiple access (NOMA)-based cognitive heterogeneous network under spectrum sensing errors and channel uncertainties. Our objective is to maximize the minimum energy efficiency of femtocells subject to the maximum power constraint, the cross-tier interference constraint and the minimum rate constraint. The infinite-dimensional robust constraints with channel uncertainties are converted into convex ones by using a worst-case transformation approach. Then, the deterministic non-convex problem is transformed into a convex one by using convex optimization theory. Numerical results demonstrate that the proposed algorithm can achieve fast convergence and strong robustness.
AbstractList In this letter, we design a robust resource allocation algorithm for a non-orthogonal multiple access (NOMA)-based cognitive heterogeneous network under spectrum sensing errors and channel uncertainties. Our objective is to maximize the minimum energy efficiency of femtocells subject to the maximum power constraint, the cross-tier interference constraint and the minimum rate constraint. The infinite-dimensional robust constraints with channel uncertainties are converted into convex ones by using a worst-case transformation approach. Then, the deterministic non-convex problem is transformed into a convex one by using convex optimization theory. Numerical results demonstrate that the proposed algorithm can achieve fast convergence and strong robustness.
Author Yang, Meng
Ye, Yinghui
Xu, Yongjun
Hu, Rose Qingyang
Li, Dong
Yang, Yang
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SubjectTerms Algorithms
Cellular communication
channel uncertainties
Cognitive heterogeneous networks
Computational geometry
Convexity
energy efficiency
Errors
Femtocells
Heterogeneous networks
Interference
Maximum power
NOMA
Nonorthogonal multiple access
Optimization
Resource allocation
Resource management
Robustness (mathematics)
Sensors
spectrum sensing errors
Uncertainty
Title Max-Min Energy-Efficient Optimization for Cognitive Heterogeneous Networks With Spectrum Sensing Errors and Channel Uncertainties
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