Busy tone based coexistence algorithm for WRAN and WLAN systems in TV white space

Karatalay, Onur; Erkucuk, Serhat; Baykaş, Tunçer

doi:10.1049/iet-com.2017.0740

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…These unused channels TV white spaces (TVWS), represent a valuable opportunity for rural connectivity. As digital TV has higher spectrum efficiency compared to analog TV, the trends of switching over from analog to digital TV have freed up more channels in the bands of TVWS [109,110,111,112,113,114,115,116,117,118,119]. Spectrum sharing through the TVWS spectrum is an important topic as it is the first step toward an efficient use of the spectrum in an opportunistic and dynamic manner through cognitive radio technology.…”

Section: Unlocking Tv White Spaces Via Cognitive Radiomentioning

confidence: 99%

A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions

Arjoune

Kaabouch

2019

Sensors

341

196

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Cognitive radio technology has the potential to address the shortage of available radio spectrum by enabling dynamic spectrum access. Since its introduction, researchers have been working on enabling this innovative technology in managing the radio spectrum. As a result, this research field has been progressing at a rapid pace and significant advances have been made. To help researchers stay abreast of these advances, surveys and tutorial papers are strongly needed. Therefore, in this paper, we aimed to provide an in-depth survey on the most recent advances in spectrum sensing, covering its development from its inception to its current state and beyond. In addition, we highlight the efficiency and limitations of both narrowband and wideband spectrum sensing techniques as well as the challenges involved in their implementation. TV white spaces are also discussed in this paper as the first real application of cognitive radio. Last but by no means least, we discuss future research directions. This survey paper was designed in a way to help new researchers in the field to become familiar with the concepts of spectrum sensing, compressive sensing, and machine learning, all of which are the enabling technologies of the future networks, yet to help researchers further improve the efficiently of spectrum sensing.

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Section: Unlocking Tv White Spaces Via Cognitive Radiomentioning

confidence: 99%

A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions

Arjoune

Kaabouch

2019

Sensors

341

196

View full text Add to dashboard Cite

show abstract

“…3) Interoperable TVWS: For interoperable TVWS, a hierarchical model for spectrum sharing is proposed for the coexistence of a heterogeneous network where a fxed user can rent spectrum from tv broadcaster and share the spectrum with the mobile user in the vicinity [104]. Another busy tone-based algorithm for IEEE 802.af and IEEE 802.22 is emerged by proposing in [105] to coexist in the TVWS band.…”

Section: E Interoperability Of Vhmsmentioning

confidence: 99%

A Secure and Intelligent Framework for Vehicle Health Monitoring Exploiting Big-Data Analytics

Rahman

Rahim

Rahman

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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The dependency on vehicles is increasing tremendously due to its excellent transport capacity, fast, effcient, fexible, pleasant journey, minimal physical effort, and substantial economic impact. As a result, the demand for smart and intelligent feature enhancement is growing and becoming a prime concern for maximum productivity based on the current perspective. In this case, the Internet of Everything (IoE) is an emerging concept that can play an essential role in the automotive industry by integrating the stakeholders, process, data, and things via networked connections. But the unavailability of intelligent features leads to negligence about proper maintenance of vehicle vulnerable parts, reckless driving and severe accident, lack of instructive driving, and improper decision, which incurred extra expenses for maintenance besides hindering national economic growth. For this, we proposed a conceptual framework for a central VHMS exploiting IoE-driven Multi-Layer Heterogeneous Networks (HetNet) and a machine learning technique to oversee individual vehicle health conditions, notify the respective ownerdriver real-timely and store the information for further necessary action. This article transparently portrayed an overview of central VHMS and proposed the taxonomy to achieve such an objective. Subsequently, we unveiled the framework for central VHMS, IoE-driven Multi-tire HetNet, with a secure and trustworthy data collection and analytics system. Finally, anticipating this proposition's outcome is immense in the automotive sector. It may motivate the researcher to develop a central intelligent and secure vehicular condition diagnostic system to move this sector towards Industry 4.0.

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“…Unlicensed users, which use Cognitive Radio to access the spectrum, are referred to as secondary users (SUs). Furthermore, the transition from analog to digital television has released many frequencies, known as TV white spaces, which have too high propagation and penetration qualities [6]. For this reason, the FCC authorized in 2008 the use of these frequencies by non-licensed users following a list of rules like using the geo-location capability to obtain the available TV bands, from White Space DataBase (WSDB), before operating [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Review on SDR, Spectrum Sensing, and CR-based IoT in Cognitive Radio Networks

Kassri¹,

En‐Nouaary²,

Bah³

et al. 2021

IJACSA

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The inherent scarcity of frequency spectrum, along with the fixed spectrum allocation adopted policy, has led to a dire shortage of this indispensable resource. Furthermore, with the tremendous growth of wireless applications, this problem is intensified as the unlicensed frequency spectrum becomes overcrowded and unable to meet the requirement of emerging radio devices operating at higher data rates. Additionally, the already assigned spectrum is underutilized. That has prompted researchers to look for a way to address spectrum scarcity and enable efficient use of the available spectrum. In this context, Cognitive Radio (CR) technology has been proposed as a potential means to overcome this issue by introducing opportunistic usage to less congested portions of the licensed spectrum. In addition to outlining the fundamentals of Cognitive Radio, including Dynamic Spectrum Access (DSA) paradigms and CR functions, this paper has a three-fold objective: first, providing an overview of Software Defined Radio (SDR), in which the architecture, benefits, and ongoing challenges of SDR are presented; second, giving an extensive review of spectrum sensing, covering sensing types, narrowband and wideband sensing schemes with their pros and cons, Machine Learningbased sensing, and open issues that need to be further addressed in this field; third, exploring the use of Cognitive Radio in the Internet of Things (IoT) while highlighting the crucial contribution of CR in enabling IoT. This Review is elaborated in an informative fashion to help new researchers entering the area of Cognitive Radio Networks (CRN) to easily get involved.

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Busy tone based coexistence algorithm for WRAN and WLAN systems in TV white space

Cited by 4 publications

References 19 publications

A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions

A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions

A Secure and Intelligent Framework for Vehicle Health Monitoring Exploiting Big-Data Analytics

A Review on SDR, Spectrum Sensing, and CR-based IoT in Cognitive Radio Networks

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