Dynamic Channel Selection and Transmission Scheduling for Cognitive Radio Networks

Zhu, Xinyu; Huang, Yang; Wu, Qihui; Zhou, Fuhui; Ge, Xiaohu; Liu, Yuan

doi:10.1109/jiot.2022.3190523

Cited by 7 publications

(3 citation statements)

References 42 publications

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“…There are many surveys and existing studies on channel assignment in CRN. 18 In this section, we explore in detail the existing work on channel assignment in CRN. We discuss different research works that use various objective criteria to optimize the channel assignment in CRNs.…”

Section: Related Workmentioning

confidence: 99%

“…Each element of matrix μF will be computed using Equation (18). For instance, take μF 1 1 , where ði, kÞ ¼ ð1,1Þ indicates the fuzzy membership function for the first objective function, that is, F 1 and the first solution point, that is, X, or in other words, the first element of the Z matrix, that is, Z 11 .…”

Section: Decision-making Using Fuzzy Logicmentioning

confidence: 99%

“…The aim of effective channel assignment is to assign channels to SUs in such a way that they do not interfere with the operation of PUs and at the same time ensure optimal performance of the spectrum. There are many surveys and existing studies on channel assignment in CRN 18 . In this section, we explore in detail the existing work on channel assignment in CRN.…”

Section: Related Workmentioning

confidence: 99%

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Multi‐objective spectrum assignment in heterogeneous cognitive radio networks for internet of things

Farooq,

Ul Hasan

2024

Int J Communication

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SummaryInternet of Things (IoT) applications have massively increased in the last few years. Future‐generation IoTs are going to be massive in number, heterogeneous in nature, and extremely demanding in terms of computation and communication requirements. Therefore, effective techniques are needed to optimize the use of scarce communication resources. This work proposes a novel multi‐objective framework to investigate the channel assignment problem in cognitive radio network (CRN)‐based IoT applications. The multi‐objective optimization framework comprises three objective functions. The first objective aims to maximize the overall system throughput fairness, the second objective aims to maximize the overall system residual energy, and the third objective aims to increase the user satisfaction level by maximizing the overall priority index. The problem of channel assignment is modeled and solved using Mixed Integer Linear Programming (MILP) and ‐constraint technique. This technique generates a set of Pareto efficient solutions, and an optimal solution among these solutions is selected using a fuzzy logic decision mechanism. Moreover, power level selection is incorporated by solving the problem multiple times for different power levels and obtaining a preferred solution for each power level. The simulations are conducted to unveil an interesting trade‐off between the conflicting system design objectives, that is, the overall throughput and the overall residual energy while incorporating the significance of primary user (PU) activity when preforming channel assignment in CRN.

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Section: Related Workmentioning

confidence: 99%

Section: Decision-making Using Fuzzy Logicmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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