Learning-Based, Distributed Spectrum Observation System for Dynamic Spectrum Sharing in the 5G Era and Beyond

Kitsunezuka, Masaki; Tsukamoto, Kenta; Sakai, Jun; Ohtsuji, Taichi; Kunihiro, Kazuaki

doi:10.1587/transcom.2018ttp0003

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…For understanding the large spectrum sharing idea, this proposed work focuses mainly on the effective use for all spectrum assets by exploiting every available hole spectrum in licensed and then unlicensed bands. 10 At last, the open issues and potential challenges have been considered, focused on the sharing spectrum in cells, and also promote research administrations is suggested.…”

Section: Related Workmentioning

confidence: 99%

“…Still, the challenges prepare open problems that make interest for researchers to model likes full‐duplex, spectrum depends on a database, compressive, spectrum appropriation depends on the theory of auction, hybrid DSA, spectrum appropriation depends on the aggregation technologies and then hybrid mechanism. For understanding the large spectrum sharing idea, this proposed work focuses mainly on the effective use for all spectrum assets by exploiting every available hole spectrum in licensed and then unlicensed bands 10 . At last, the open issues and potential challenges have been considered, focused on the sharing spectrum in cells, and also promote research administrations is suggested.…”

Section: Related Workmentioning

confidence: 99%

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A machine learning‐based compressive spectrum sensing in 5G networks using cognitive radio networks

Perumal¹,

Nagarajan²

2022

Int J Communication

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Summary In recent times, evolution of communication technology and standard has grown in leaps and bounds from a conventional 1G communication technology towards the recent 5G and 6G technologies in a very short span of time. However, due to increasing scarcity of spectrum for these devices, cognitive radio networks (CRNs) have emerged to be promising solutions to allocate the required spectrum to the users in an intelligent manner. The method of compressive sensing‐based cyclo‐stationary feaure detection method is implemented based on a powerful CNN classifier to detect the presence or absence of PU activity. Detection probability and MSE have been improved, and the optimal detection has been reformulated for minimizing the possibility of error. Performance metrics have been compared against benchmark methods and superior performance reported. The sensing conduction and the accuracy of the proposed design are increased as 98.5%.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A machine learning‐based compressive spectrum sensing in 5G networks using cognitive radio networks

Perumal¹,

Nagarajan²

2022

Int J Communication

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“…The sustained increase in mobile data traffic is driving the emergence of 5th generation (5G) wireless communications [1]. In the 5th Generation Mobile Communications Systems era, there will be a necessity for dynamic usage of limited radio frequency resources [2,3]. 5G is a next-generation mobile communication technology that aims to provide more capacity and faster bandwidth than older decades of Long Term Evolution (LTE).…”

Section: Introductionmentioning

confidence: 99%

Spectrum sharing framework in full duplex mode with minimum interference in 5G cellular network

Rajput,

Malathi

2024

Multimed Tools Appl

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Spectral sharing with in-band full-duplex (FD) primary users (PUs) in cognitive radio (CR) systems is a difficult and challenging task. The ability of the secondary user (SU) to access the spectrum could be substantially impeded by the primary network's self-interference. We propose a novel dynamic spectrum sharing (DSS) scheme while satisfying In-band FD technology is the mitigation of strong self-interference in the 5G cellular networks platform. In particular, the in-band FD-PU pair implements the normal proper Gaussian signal, although it is intended for SU downlink transmission with an inappropriate Gaussian signal. First, we derive the closed-form expression and the upper bounds of the default probabilities for SU and PU, respectively. While discussing major concerns in the 5G cellular networks system, the second stage optimization is carried out utilizing the optimal spectrum sharing approach, and a self-interference game methodology based on the proportional enthalpy based sigmoid solution is applied. This method is primarily employed to reduce computational complexity and overheads. In terms of SINR, Spectral efficiency, and other metrics, the computational studies shows that the provided method outperforms existing methods.

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Radio Environment Map Construction Based on Spatial Statistics and Bayesian Hierarchical Model

Zhang

Ding

et al. 2021

IEEE Trans. Cogn. Commun. Netw.

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Learning-Based, Distributed Spectrum Observation System for Dynamic Spectrum Sharing in the 5G Era and Beyond

Cited by 6 publications

References 24 publications

A machine learning‐based compressive spectrum sensing in 5G networks using cognitive radio networks

A machine learning‐based compressive spectrum sensing in 5G networks using cognitive radio networks

Spectrum sharing framework in full duplex mode with minimum interference in 5G cellular network

Radio Environment Map Construction Based on Spatial Statistics and Bayesian Hierarchical Model

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