5G Needs Database-Driven Spectrum Sharing!

Holland, Oliver; Weaver, Barry L.; Mitchell, A. E.; Armitage, Michael; Davison, Steve; Gray, Steve; Uplejs, Andris; Jagger, Steve; Kokkinen, Heikki

doi:10.1109/dyspan.2018.8610479

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…However, the spectrum availability for massive densities of devices still remains an open challenge [90]. In this respect, white space is a promising solution for transmission of sensor data over long distances [91,92] to supplement the capacity offered by 5G networks [90,93].…”

Section: Future Workmentioning

confidence: 99%

Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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The author of this dissertation contributed to the development of the heuristic algorithms, the implementation of the simulator, the evaluation through simulation, the analysis of results, and writing the article.Publication IV empirically evaluates the impact of edge computing on emerging interactive applications and services. At the time of writing, there was no clear consensus on what specifically constitutes the edge of the network in edge computing. Thus, we first survey the state of the art in edge computing architectures and determine different deployment options for edge devices. Next, we experimentally evaluate edge computing when available at different physical locations and with different virtualization technologies. Specifically, we characterize the end-to-end latency (including

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Section: Future Workmentioning

confidence: 99%

Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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“…The calculated interference power depends on the angle between the azimuth and elevation of the maximal DTT RX antenna gain and the interference source azimuth and elevation. Such a cone angle can be calculated using formula (37b) from [9].…”

Section: Dtt Coverage Calculationmentioning

confidence: 99%

Dynamic spectrum access in terrestrial TV band: assessment of prospects in Kenya

Kryszkiewicz

Kokkinen²,

Ojaniemi³

et al. 2021

Telecommun Syst

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Wireless connectivity has become a significant part of human life all over the world, both in developing and developed countries. In order to provide sufficient coverage without the densification of cellular networks, relatively low carrier frequencies should be used. This paper considers the reuse of the digital terrestrial television (DTT) band for cellular system operation in Kenya, while protecting incumbent TV signal reception according to the Dynamic Spectrum Alliance (DSAL) rules. A state of the art model for DTT coverage and allowed cellular system power calculation is tested using real data for Kenya. Suggestions regarding future DSAL rules amendments are provided. Moreover, the amount of spectrum resources available for cellular system operation in the DTT band in Kenya is estimated against varying system parameters.

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“…Experiments of LSA systems in Finland, France and Italy had demonstrated its feasibility and superiority [9]. Considering the constraint of the propagation characteristics of the mm-Wave band and the potential of TVWS, the database-driven spectrum sharing scheme and deployment scenarios for 5G were presented in [10]. It is safe to envision that more and more spectrum bands will be opened for secondary access to alleviate the spectrum scarcity problem as well as to promote the social worth of the spectrum resource.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Knowledge and Real-Time Observing Enabled Smart Spectrum Management

et al. 2020

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Spectrum is the indispensable resource for 5G wireless systems and beyond. The dynamic spectrum management (DSM) framework with spectrum sharing among different kinds of users is essential to satisfy the sustainable rapid increase of the bandwidth requirement. Based on the analysis of the DSM as well as the latent applications of the machine learning and artificial intelligence (AI) in the spectrum access, this paper will address the problem of incorporating intelligence into the spectrum management. Firstly, the spectrum opportunity (SOP) related information is layered into the spectrum data, the spectrum information and the spectrum knowledge based on the processing and abstractive level. The spectrum knowledge is formally defined as the extendible and scalable information to reason and predict the SOP usability as well as the outcome of the SOP occupancy. Then the smart spectrum model (SSM) is proposed with the spectrum knowledge as the key enabler and the coupled SOP exploration and exploitation as the core feature. Under the SSM framework, the spectrum knowledge and real-time observing (SKRO) enabled SOP exploration scheme is designed, which can make use of both the historical information and the real-time sensing information for smart SOP exploration. Extensive simulations are provided which demonstrate that the SKRO enabled SSM can achieve much better SOP utilization while satisfying the required legacy assurance. Specifically, in the low signal to noise environment, at least 16.55% gains on the SOP utilization ratio can be obtained compared with the DSM.

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5G Needs Database-Driven Spectrum Sharing!

Cited by 6 publications

References 6 publications

Efficient placement of edge computing devices for vehicular applications in smart cities

Efficient placement of edge computing devices for vehicular applications in smart cities

Dynamic spectrum access in terrestrial TV band: assessment of prospects in Kenya

Spectrum Knowledge and Real-Time Observing Enabled Smart Spectrum Management

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