On the use of radio environment maps for interference management in heterogeneous networks

Perez-Romero, J.; Zalonis, Andreas; Boukhatem, Lila; Kliks, Adrian; Koutlia, Katerina; Dimitriou, Nikos; Kurda, Reben

doi:10.1109/mcom.2015.7180526

Cited by 77 publications

(47 citation statements)

References 8 publications

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“…In practice, the most important parameter of the radio environment map is the signal radiation level in units of decibels (dB). If the Kriging algorithm is used directly, the expression of (ℎ) can be simply obtained by (5) in units of dB 2 . However, this is not consistent with the dB units of propagation loss that are calculated by the radio propagation model.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…A radio environment map is an integrated database that is used to describe the electromagnetic environment. Because of its wide range of applications for radio [4][5][6][7][8], it has been further extended. The radio environment map is a comprehensive database that contains many fields of information, such as the available spectrum profile, geographical features, rules, relevant laws and regulations, radio equipment situation, and expert experience [9].…”

Section: Introductionmentioning

confidence: 99%

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Parameter Estimation for the Field Strength of Radio Environment Maps

Gao

Xie

2017

Wireless Communications and Mobile Computing

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The parameters of a radio environment map play an important role in radio management and cognitive radio. In this paper, a method for estimating the parameters of the radio environment map based on the sensing data of monitoring nodes is presented. According to the principles of radio transmission signal intensity losses, a theoretical variogram model based on a propagation model is proposed, and the improved theoretical variation function is more in line with the attenuation of radio signal propagation. Furthermore, a weight variogram fitting method is proposed based on the characteristics of field strength parameter estimation. In contrast to the traditional method, this method is more closely related to the physical characteristics of the electromagnetic environment parameters, and the design of the variogram and fitting method is more in line with the spatial distribution of electromagnetic environment parameters. Experiments on real and simulation data show that the proposed method performs better than the state-of-the-art method.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parameter Estimation for the Field Strength of Radio Environment Maps

Gao

Xie

2017

Wireless Communications and Mobile Computing

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“…For modeling the PU activity, existing works mostly use ON/OFF models such as two state Markov model, Bernoulli and exponential models, and recently, the concept of using learning based PU modeling is getting attention in the literature [41,155]. In practice, parameters related to the PU traffic/channel can be estimated by employing the following approaches: (i) statistical analysis of sensing measurements obtained from spectrum occupancy measurement campaigns [30], (ii) spectrum prediction models like hidden Markov model and Bayesian interference model [156], and (ii) Radio Environment Map (REM) which can be created either based on sensing information obtained from the sensor nodes or database information obtained from regulators/operators or both [32,157].…”

Section: A Primary Traffic Modelmentioning

confidence: 99%

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Sharma

Bogale

et al. 2018

IEEE Commun. Surv. Tutorials

214

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Full-Duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) of wireless communications due to its advantages including potential doubling of the capacity, reduced end-to-end and feedback delays, improved network secrecy and efficiency, and starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems.

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“…On the other hand, spectrum measurements ensures a data-driven approach, complementarily to the traditional propagation model-based approach [242], when aiming for improving the accuracy and the update speed of the spectrum availability provided by the geolocation spectrum databases [5], [88], [246]. Moreover, spectrum measurements are also coupled with the building of radio environment maps (REM) [255]- [257].…”

Section: A Sources Of Spectrum Datamentioning

confidence: 99%

“…In contrast to the geolocation spectrum database, REM is an advanced knowledge base that stores live multi-domain information on the entities in the network as well as on the environment [255], [256].…”

Section: Relationship With Radio Environment Mapsmentioning

confidence: 99%

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

Ding

Jiao

Wang

et al. 2018

IEEE Commun. Surv. Tutorials

159

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Abstract-Spectrum inference, also known as spectrum prediction in the literature, is a promising technique of inferring the occupied/free state of radio spectrum from already known/measured spectrum occupancy statistics by effectively exploiting the inherent correlations among them. In the past few years, spectrum inference has gained increasing attention owing to its wide applications in cognitive radio networks (CRNs), ranging from adaptive spectrum sensing, and predictive spectrum mobility, to dynamic spectrum access and smart topology control, to name just a few. In this paper, we provide a comprehensive survey and tutorial on the recent advances in spectrum inference. Specifically, we first present the preliminaries of spectrum inference, including the sources of spectrum occupancy statistics, the models of spectrum usage, and characterize the predictability of spectrum state evolution. By introducing the taxonomy of spectrum inference from a time-frequency-space perspective, we offer an in-depth tutorial on the existing algorithms. Furthermore, we provide a comparative analysis of various spectrum inference algorithms and discuss the metrics of evaluating the efficiency of spectrum inference. We also portray the various potential applications of spectrum inference in CRNs and beyond, with an outlook to the 5th generation mobile communications (5G) and next generation high frequency (HF) communications systems. Last but not least, we highlight the critical research challenges and open issues ahead.

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On the use of radio environment maps for interference management in heterogeneous networks

Cited by 77 publications

References 8 publications

Parameter Estimation for the Field Strength of Radio Environment Maps

Parameter Estimation for the Field Strength of Radio Environment Maps

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

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