A serious gaming approach to managing interference in ad hoc femtocell wireless networks

Alotaibi, Abdullah Alhumaidi; Angelides, Marios C.

doi:10.1016/j.comcom.2018.07.013

Cited by 5 publications

(2 citation statements)

References 67 publications

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“…In Reference 10, the authors have estimated the consumption of energy at several channel decision states, but the energy dissipated in the channel sensing has not been investigated. The work presented in Reference 11 mainly considers the different coding and modulation techniques for reducing the power consumption. In Reference 12, a framework is proposed to calculate the energy consumption in the spectrum sensing process.…”

Section: Related Workmentioning

confidence: 99%

Cooperation and energy harvesting based spectrum sensing schemes for green cognitive radio networks

Srivastava

Kaur

2022

Trans Emerging Tel Tech

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Cognitive radio network (CRNs) with energy harvesting approach to identify unused spectrum bands and utilize them opportunistically is observed as an evolving technology to handle spectrum scarcity problems. In CRNs, the secondary users (SUs) continuously sense the primary user's (PUs) spectrum to secure the data transmission of PUs and to access the vacant PU's spectrum for their data transmission. For designing future green networks, it is essential that the spectrum sensing process must be accurate, rapid, and energy‐efficient. Therefore, in this work, three sensing schemes are proposed. The first is a cooperation‐based joint cooperation spectrum sensing (JCSS) scheme in which the cooperative CRNs permit the SUs, working in an identical band, to cooperate, and this cooperation approach decreases sensing time and improves sensing probability for vacant spectrum. The result shows that the sensing probability for a vacant spectrum is increased by 34%. The proposed JCSS scheme considers the inherent asymmetry property of the network; therefore, it helps to improve the overall rapidity gain of the networks. The other two proposed sensing schemes, preset spectrum sensing (PSS) and viscous spectrum sensing (VSS), are based on energy harvesting that analyzes the percentage of energy‐saving for various states. The suggested schemes are better in terms of scalability because, in these schemes, it is not essential to sense all spectrums, which leads to a reduction in sensing time.

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Section: Related Workmentioning

confidence: 99%

Cooperation and energy harvesting based spectrum sensing schemes for green cognitive radio networks

Srivastava

Kaur

2022

Trans Emerging Tel Tech

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“…Wu et al introduce a deep learning algorithm for multiview medical images processing [14]. Alhumaidi et al use a serious gaming approach to manage interferences in ad hoc femtocell, Stackelberg competition is used to elect the best FAPs without making a random choice [15]. Unfortunately, the proper integration of the features with different input space is missing.…”

Section: Related Workmentioning

confidence: 99%

Design of Multi-View Graph Embedding for Features Selection and Remotely Sensing Signal Classification

Alotaibi¹,

Alotaibi²

2020

IJACSA

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Now-a-days, signal processing remains an intensive challenging area of research. In fact, various strategies have been suggested to address semi-supervised, feature selection and unlabeled samples challenges. The most frequent achievement was dedicated to exploit a single kind of feature/view from the original data. Recently, advanced techniques aimed to explore signals from different views and to, properly, integrate divergent kinds of interdependent features. In this paper, we propose a novel design of a multi-View Graph Embedding for features selection allowing a convenient integration of complementary weighted features. The proposed framework combines the singular properties of each feature space to accomplish a physically meaningful cooperative low-dimensional selection of input data. This allows us not only to perform a semi-supervised classification, but also to propagates narrow class information to unlabeled sample when only partial labeling knowledge is available. This paper makes the following contributions: (i) a feature selection schema for data refinement; and (ii) the adaptation of a multi-view graph-based approach by a better tackling of semi-supervised and dimensionality issues. Our experimental results, conducted by using a mixture of complementary features and aerial images datasets, demonstrate the effectiveness of the proposed framework without significantly increasing computational complexity.

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Novel EBBDSA based Resource Allocation Technique for Interference Mitigation in 5G Heterogeneous Network

Hasan

Islam

Gadekallu

et al. 2023

Computer Communications

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A serious gaming approach to managing interference in ad hoc femtocell wireless networks

Cited by 5 publications

References 67 publications

Cooperation and energy harvesting based spectrum sensing schemes for green cognitive radio networks

Cooperation and energy harvesting based spectrum sensing schemes for green cognitive radio networks

Design of Multi-View Graph Embedding for Features Selection and Remotely Sensing Signal Classification

Novel EBBDSA based Resource Allocation Technique for Interference Mitigation in 5G Heterogeneous Network

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