Asymmetric Cooperative Communications Based Spectrum Leasing via Auctions in Cognitive Radio Networks

Jayaweera, Sudharman K.; Bkassiny, Mario; Avery, Keith

doi:10.1109/twc.2011.061311.102044

Cited by 93 publications

(72 citation statements)

References 21 publications

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“…Dynamic spectrum leasing for CR networks has only recently attracted a number of contributions [8], [9], [10], [11]. In [8], authors present a spectrum leasing model for the secondary nodes where the division of leasing time follows a leader-follower approach.…”

Section: Previous Work and Our Contributionmentioning

confidence: 99%

Dynamic Spectrum Leasing for Bi-Directional Communication: Impact of Selfishness

Hafeez

Elmirghani

2016

IEEE Trans. Commun.

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Abstract-In this paper, we propose a beamforming based dynamic spectrum leasing (DSL) technique to improve the spectral utility of bi-directional communication of the legacy/primary spectrum users through the help of co-located secondary users. The secondary users help for a time interval to relay the data between two primary terminals using physical layer network coding and beamforming to attain bi-directional communication with high spectral utility. As a reimbursement, the secondary users, cognitive radios (CRs) in our case, get exclusive access to the primary spectrum for a certain duration. We use Nash Bargaining to determine the optimal division of temporal resources between relaying and reimbursement. Moreover, we consider that a fraction of secondary nodes can act selfishly by not helping the primary yet enjoy the reimbursement time. We measure the utility of the DSL scheme in terms of a metric called timebandwidth product (TBP) ratio quantifying the number of bits transmitted in direct communication vs. DSL. We show that if all secondary nodes act honestly, more than 17 folds increase in the TBP ratio is observed for a sparse CR network (CRN). However, in such a network, selfish behavior of CR nodes can reduce the gain by more than a factor of 2.

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Section: Previous Work and Our Contributionmentioning

confidence: 99%

Dynamic Spectrum Leasing for Bi-Directional Communication: Impact of Selfishness

Hafeez

Elmirghani

2016

IEEE Trans. Commun.

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“…Los resultados del aprendizaje se utilizan para actualizar la detección (es decir, la observación) y el acceso a los canales, es decir, la decisión, reglas de las aplicaciones DSA (Bkassiny, Jayaweera y Avery, 2011;Chen, Zhao y Swami, 2008;Haykin, 2005;.…”

Section: Aprendizaje En Crnunclassified

Tecnicas inteligentes en la asignacion de espectro dinamica para redes inalambricas cognitivas

Salgado

Marquez

Gómez³

2016

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RESUMENObjetivo: El objetivo de este trabajo es estudiar las aplicaciones de las diferentes técnicas de inteligencia artificial y aprendizaje autónomo en la asignación dinámica de espectro para redes inalámbricas cognitivas, es especial las distribuidas. Método: El desarrollo del presente trabajo se realizó a través del estudio y análisis de algunas de las publicaciones más relevantes en la literatura actual por medio de la búsqueda en revistas internacionales indexadas en ISI y Scopus. Resultados: Se determinaron las técnicas de inteligencia artificial y aprendizaje autónomo más relevantes y con mayor aplicación en la asignación de espectro para redes inalámbricas cognitivas. Conclusiones: La implementación de una técnica o del conjunto de las mismas depende de las necesidades en procesamiento de la señal, compensaciones en los tiempos de respuesta, disponibilidad de las muestras, capacidad de almacenamiento, capacidad de aprendizaje, robustez, entre otras.Palabras Clave: aprendizaje autonomo, asignacion dinamica de espectro, inteligencia artificial, radio cognitivas, redes inalambricas. ABSTRACTObjective: The objective of this work is to study the applications of different techniques of artificial intelligence and autonomous learning in the dynamic allocation of spectrum for cognitive wireless networks, especially the distributed ones. Method: The development of this work was done through the study and analysis of some of the most relevant publications in current literature through the search in indexed international journals in ISI and Scopus. Results: the most relevant techniques of artificial intelligence and autonomous learning were determined. Also, the ones with more applicability in the allocation of spectrum for cognitive wireless networks were determined, too. . Tecnicas inteligentes en la asignacion de espectro dinamica para redes inalambricas cognitivasSmart techniques in the dynamic spectrum alocation for cognitive wireless networks

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“…For instance, in [8], the PUs choose the SUs that allocate higher transmission power to relay PUs' packets based on the bid values received from SUs through auction. The disadvantages are that the PUs incur high energy consumption while exchanging control messages and making decisions on the outcomes of auctions.…”

Section: Enhancing Auction and Coordination Mechanismsmentioning

confidence: 99%

“…While there are investigations into distributed SU networks [8], this is not the case for PU networks in which most schemes in the literature assume the presence of a PU BS or a single PU node pair. The major challenge in distributed SU networks is that SU BS does not exist, and so the SUs must coordinate among themselves to determine a control channel for the purpose of control message exchange in spectrum leasing.…”

Section: Investigating Distributed Spectrum Leasing Schemesmentioning

confidence: 99%

Spectrum Leasing in Cognitive Radio Networks: A Survey

Syed

Yau

2014

International Journal of Distributed Sensor Networks

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Cognitive Radio (CR) is a dynamic spectrum access approach, in which unlicensed users (or secondary users, SUs) exploit the underutilized channels (or white spaces) owned by the licensed users (or primary users, PUs). Traditionally, SUs are oblivious to PUs, and therefore the acquisition of white spaces is not guaranteed. Hence, a SU must vacate its channel whenever a PU reappears on it in an unpredictable manner, which may affect the SUs' network performance. Spectrum leasing has been proposed to tackle the aforementioned problem through negotiation between the PU and SU networks, which allows the SUs to acquire white spaces for a guaranteed period of time. Through spectrum leasing, the PUs and SUs enhance their network performances, and additionally PUs maximize their respective monetary gains.

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Asymmetric Cooperative Communications Based Spectrum Leasing via Auctions in Cognitive Radio Networks

Cited by 93 publications

References 21 publications

Dynamic Spectrum Leasing for Bi-Directional Communication: Impact of Selfishness

Dynamic Spectrum Leasing for Bi-Directional Communication: Impact of Selfishness

Tecnicas inteligentes en la asignacion de espectro dinamica para redes inalambricas cognitivas

Spectrum Leasing in Cognitive Radio Networks: A Survey

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