Radio Resource Allocation Techniques for Efficient Spectrum Access in Cognitive Radio Networks

Tsiropoulos, Georgios I.; Dobre, Octavia A.; Ahmed, Mohamed H.; Baddour, Kareem E.

doi:10.1109/comst.2014.2362796

Cited by 204 publications

(97 citation statements)

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“…" Radio Resource Allocation T echniques for Efficient Spectrum Access in Cognitive Radio Networks" [38] => T his paper focuses on resource allocation techniques in CRNs such as SINR-based, transmission powerbased, centralised and distributed methods of decision making. => CRNs optimisation methods are overviewed, accompanied by a comp rehensive study of the resource allocation problem formulations.…”

Section: Taxonomy Of Spectrum Access Methods and Authorisation Rmentioning

confidence: 99%

“…In [38], a survey on resource allocation challenges in CRNs according to different design techniques such as, SINR-based, transmission power-based, centralised and distributed methods of decision making, is presented. The authors provide mathematical formulation of each resource allocation problem.…”

Section: A) Review Of the State-of-the-art (Sota) Survey Articlesmentioning

confidence: 99%

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Licensed Spectrum Sharing Schemes for Mobile Operators: A Survey and Outlook

Tehrani

Vahid

Triantafyllopoulou

et al. 2016

IEEE Commun. Surv. Tutorials

191

119

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The ongoing development of mobile communication networks to support a wide range of superfast broadband services has led to massive capacity demand. This problem is expected to be a significant concern during the deployment of the 5G wireless networks. The demand for additional spectrum to accommodate mobile services supporting higher data rates and having lower latency requirements, as well as the need to provide ubiquitous connectivity with the advent of the Internet of Things (IoT) sector, is likely to considerably exceed the supply, based on the current policy of exclusive spectrum allocation to mobile cellular systems. Hence, the imminent spectrum shortage has introduced a new impetus to identify practical solutions to make the most efficient use of the scarce licensed bands in a shared manner. Recently, the concept of dynamic spectrum sharing has received considerable attention from regulatory bodies and governments globally, as it could potentially open new opportunities for mobile operators to exploit spectrum bands whenever they are underutilised by their owners, subject to service level agreements. Although various sharing paradigms have been proposed and discussed, the impact and performance gains of different schemes can be scenario-specific and vary depending on the nature of the sharing parties, the level of sharing and spectrum access scheme. In this survey, we describe the main concepts of dynamic spectrum sharing, different sharing scenarios, as well as the major challenges associated with sharing licensed bands. Finally, we conclude this survey paper with open research challenges and suggest some future research directions

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Section: Taxonomy Of Spectrum Access Methods and Authorisation Rmentioning

confidence: 99%

Section: A) Review Of the State-of-the-art (Sota) Survey Articlesmentioning

confidence: 99%

Licensed Spectrum Sharing Schemes for Mobile Operators: A Survey and Outlook

Tehrani

Vahid

Triantafyllopoulou

et al. 2016

IEEE Commun. Surv. Tutorials

191

119

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show abstract

“…Cognitive radio is a technique that makes it possible to share the spectrum opportunities between a primary user and a secondary user. A secondary user discovers a white space that is not utilized by a primary user with spectrum sensing, spectrum decision, and spectrum sharing techniques, thereby improving the spectrum effiency [2][3][4][5]. In this case, a spectrum allocation method of a secondary user affects a major impact on the overall performance of the cognitive radio network.…”

Section: Introductionmentioning

confidence: 99%

“…It is also assumed that secondary users are fixed and can move slower than the time to reach Nash Equilibrium. In addition, there is one pair of primary user and the channel information for the primary user is known by the secondary user through the primary user information database [3]. In this case, the transmission range of the primary user is large enough for all secondary users to hear, and it is assumed that the available channel set of all secondary users is the same.…”

Section: Introductionmentioning

confidence: 99%

Game-Theoretic Channel Allocation in Cognitive Radio Networks

Lim¹

2017

IJECE

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Cognitive radio networks provide dynamic spectrum access techniques to support the increase in spectrum demand. In particular, the spectrum sharing among primary and secondary users can improve spectrum utilization in unused spectrum by primary users. In this paper, we propose a novel game theoretic channel allocation framework to maximize channel utilization in cognitive radio networks. We degisn the utility function based on the cochannel interference among primary and secondary users. In addition, we embed the property of the adjacent channel intererence to consider real wireless environment. The results show that the utility function converges quickly to Nash equilibrium and achieves channel gain by up to 25 dB compared to initial assignment. Keyword:Channel allocation Channel interference Cognitive radio network Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Sangsoon Lim, Software R&D Center, Samsung Electronics, 56, Seongchon-gil, Seocho-gu, Seoul, South Korea. Email: lssgood80@gmail.com INTRODUCTIONAn allocation policy of existing static frequency resources is able to provide a service that assigns a specific spectrum band during the long time in a wide area to a licensed user. However, this approach not only does not satisfy the needs of the rapidly increasing frequency resources, but also degrades the efficiency of spectrum utilization [1]. In order to dramatically increase the utilization efficiency of the distributed spectrum resources that is not used or rarely occupied, it has been promoted a lot of research of cognitive radio networks based on dynamic spectrum access technology. Cognitive radio is a technique that makes it possible to share the spectrum opportunities between a primary user and a secondary user. A secondary user discovers a white space that is not utilized by a primary user with spectrum sensing, spectrum decision, and spectrum sharing techniques, thereby improving the spectrum effiency [2][3][4][5]. In this case, a spectrum allocation method of a secondary user affects a major impact on the overall performance of the cognitive radio network.Recently, several clever schemes employing a game-theoretic framework were proposed to share efficiently distributed spectrum bands [6][7][8]. A game-theoretic framework is a tool, which can provide a useful resource allocation algorithm by designing a concrete utility function, so as to optimize a distributed spectrum allocation. M. Felegyhazi [6] has proposed a game-theoretic approach that takes into account the same channel interference from the point of view of a single hop to manage the channel allocation in a typical wireless network. Transmitter and possible transmission data rate (Data rate) is would be determined by defining a couple of recipients as a player participating in the game depending on the number of players sharing the radio channel . Accordingly , each player makes the competition game to maximize the data rate that can he achieved. L. Gao [7] follows the framework ...

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“…It allows the unlicensed or secondary users (SUs) to dynamically access the vacant licensed spectrum of primary users (PUs) without the authorization of operators/administrations [2]. To realize cognitive radio networks (CRNs), channel allocation should be adapted according to the varying channel states and requirements, predefined quality of service (QoS) or quality of experience (QoE) [3] of users and other criterion [4][5][6]. The main purpose of channel allocation is assigning the usable channels or time-frequency chunks to SUs.…”

Section: Introductionmentioning

confidence: 99%