Modelo e Análise de Disponibilidade para Acesso ao Meio baseado em Contenção em Redes de Rádio Cognitivo
Resumo
Em geral, o cálculo da disponibilidade em rádio cognitivo (RC) baseia-se em um modelo ON/OFF simples, que representa o comportamento do usuário primário (UP). Propomos um modelo para o estudo da disponibilidade que combina o acesso ao meio baseado em contenção, os comportamentos dos usuários secundários (USs) e do UP. O modelo composto permitiu avaliar a relação entre parâmetros (e.g., Número de US, Tempo de acesso do UP, Tempo entre aparições do UP) e a disponibilidade. De acordo com as análises de sensibilidade realizadas, além de outros resultados obtidos, conclui-se que o número de US tem maior influência sobre a disponibilidade que qualquer outro parâmetro avaliado.
Referências
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Archer, G. E. B. et al, Sensitivity Measures, Anova-Like Techniques and the use of Bootstrap, J. Statist. Comput. Simul. Vol 50. Pp 99-120. 1997.
Aripin, N. M. A Cross-Layer Approach in Sensing and Resource Allocation for Multimedia Transmission over Cognitive UWB Networks. EURASIP Journal onWireless Communications and Networking Volume 2010, 10 pages.
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Bolch, G. et al. Queueing Networks and Markov Chains. 2. Ed. New Jersey, John Wiley & Sons, 2006.
Chiola, G. et al. Generalized Stochastic Petri Nets: A Definition at the Net Level and its Implications. IEEE Transactions on Software Engineering, V. 19, Issue 2, p. 89-107. IEEE Press, February 1993.
Choi, K. W. Adaptive Sensing Technique to Maximize Spectrum Utilization in Cognitive Radio. IEEE TRANS. ON VEHICULAR TECH, VOL. 59, NO. 2, 2010.
Cordeiro, C. et al, Cognitive PHY and MAC layers for dynamic spectrum access and sharing of TV bands, Proceeding TAPAS '06 Proceedings of the first international workshop on Technology and policy for accessing spectrum, New York, NY, USA, 2006.
Domenico, A. et al, A Survey on Mac Strategies for Cognitive Radio Networks. IEEE Communications Surveys And Tutorials, Issue 99, pp 1-24, 2010.
Ghosh, C. And Roy S. Coexistence Challenges for Heterogeneous Cognitive Wireless Networks in TV White Spaces, Wireless Communications IEEE, V. 18, Issue. 4, pp. 22-31, Aug. 2011.
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IEEE std.802.22. IEEE 802.22 Working Group on Wireless Regional Area Networks, Enabling Rural Broadband Wireless Access Using Cognitive Radio Technology in TV Whitespaces, [link], last release 2011.
Khalid, L. And Anpalagan A., Emerging cognitive radio technology: Principles, challenges and opportunities, Computers and Electrical Engineering,Volume 36, Issue 2, March, 2009.
Kim, H. And Shin, K. Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks, IEEE Transactions ON Mobile Computing, VOL. 7, NO. 5, MAY 2008.
Lai, L. et al, Optimal Medium Access Control In Cognitive Radios: A Sequential Design Approach, 2008. ICASSP 2008, Las Vegas, USA, pp. 2073 – 2076, Mai. 2008.
Marsan, M. J. Modelling with Generalized Stochastic Petri Nets, Wiley Series in Parallel Computing John Wiley and Sons, 1995.
Mitola, J. Cognitive Radio: Na integrated agent architeture for Software defined Radio, Ph. D. Dissertation, KTH Royal Intitute of Technology, Stockholm, Sweden, 2000.
Ross, S. Introductory Statistics. Elsevier Science. Third Edition, 2010.
Shen, H. S. And Gao, W. MAC and PHY Proposal for 802.11af, [link], Mar. 2010.
Shin, K, G. et al, Cognitive Radio for Dynamic Spectrum Access: From Concept to Reality, Wireless Communications IEEE, V. 17, Issue. 6, pp. 64-74, Dec. 2010.
Zhao Q. et al, Decentralized cognitive mac for dynamic spectrum access, in proc.
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Zeng, Y. et al, A review on spectrum sensing for cognitive radio: challenges and solutions, EURASIP Journal on Advances in Signal Processing - Special issue on advanced signal processing for cognitive radio networks, Volume 2010, January 2010.
Akyildiz, I. et al, NeXt generation/dynamic spectrum access/cognitive Radio Wireless Networks: A Survey, Computer Networks Journal (Elsevier), 2006.
Archer, G. E. B. et al, Sensitivity Measures, Anova-Like Techniques and the use of Bootstrap, J. Statist. Comput. Simul. Vol 50. Pp 99-120. 1997.
Aripin, N. M. A Cross-Layer Approach in Sensing and Resource Allocation for Multimedia Transmission over Cognitive UWB Networks. EURASIP Journal onWireless Communications and Networking Volume 2010, 10 pages.
Bayhan, S. MAC layer design in cognitive radio networks, World of Wireless Mobile and Multimedia Networks (WoWMoM). Montreal, QC, Canada, Agosto 2010.
Bolch, G. et al. Queueing Networks and Markov Chains. 2. Ed. New Jersey, John Wiley & Sons, 2006.
Chiola, G. et al. Generalized Stochastic Petri Nets: A Definition at the Net Level and its Implications. IEEE Transactions on Software Engineering, V. 19, Issue 2, p. 89-107. IEEE Press, February 1993.
Choi, K. W. Adaptive Sensing Technique to Maximize Spectrum Utilization in Cognitive Radio. IEEE TRANS. ON VEHICULAR TECH, VOL. 59, NO. 2, 2010.
Cordeiro, C. et al, Cognitive PHY and MAC layers for dynamic spectrum access and sharing of TV bands, Proceeding TAPAS '06 Proceedings of the first international workshop on Technology and policy for accessing spectrum, New York, NY, USA, 2006.
Domenico, A. et al, A Survey on Mac Strategies for Cognitive Radio Networks. IEEE Communications Surveys And Tutorials, Issue 99, pp 1-24, 2010.
Ghosh, C. And Roy S. Coexistence Challenges for Heterogeneous Cognitive Wireless Networks in TV White Spaces, Wireless Communications IEEE, V. 18, Issue. 4, pp. 22-31, Aug. 2011.
Hamby, D. M. A review of techniques for parameter sensitivity analysis of environmental models. Environmental Monitoring and Assessment, p 135–154. 1994.
IEEE std.802.22. IEEE 802.22 Working Group on Wireless Regional Area Networks, Enabling Rural Broadband Wireless Access Using Cognitive Radio Technology in TV Whitespaces, [link], last release 2011.
Khalid, L. And Anpalagan A., Emerging cognitive radio technology: Principles, challenges and opportunities, Computers and Electrical Engineering,Volume 36, Issue 2, March, 2009.
Kim, H. And Shin, K. Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks, IEEE Transactions ON Mobile Computing, VOL. 7, NO. 5, MAY 2008.
Lai, L. et al, Optimal Medium Access Control In Cognitive Radios: A Sequential Design Approach, 2008. ICASSP 2008, Las Vegas, USA, pp. 2073 – 2076, Mai. 2008.
Marsan, M. J. Modelling with Generalized Stochastic Petri Nets, Wiley Series in Parallel Computing John Wiley and Sons, 1995.
Mitola, J. Cognitive Radio: Na integrated agent architeture for Software defined Radio, Ph. D. Dissertation, KTH Royal Intitute of Technology, Stockholm, Sweden, 2000.
Ross, S. Introductory Statistics. Elsevier Science. Third Edition, 2010.
Shen, H. S. And Gao, W. MAC and PHY Proposal for 802.11af, [link], Mar. 2010.
Shin, K, G. et al, Cognitive Radio for Dynamic Spectrum Access: From Concept to Reality, Wireless Communications IEEE, V. 17, Issue. 6, pp. 64-74, Dec. 2010.
Zhao Q. et al, Decentralized cognitive mac for dynamic spectrum access, in proc.
Symposium on Dynamic Spectrum Access Networks (DySPAN’05), Baltimore, MD, USA, pp. 224-232, Nov. 2005.
Zeng, Y. et al, A review on spectrum sensing for cognitive radio: challenges and solutions, EURASIP Journal on Advances in Signal Processing - Special issue on advanced signal processing for cognitive radio networks, Volume 2010, January 2010.
Publicado
16/07/2012
Como Citar
VASCONCELOS, Eduardo; DIAS, Kelvin L.; CUNHA, Paulo R. F..
Modelo e Análise de Disponibilidade para Acesso ao Meio baseado em Contenção em Redes de Rádio Cognitivo. In: WORKSHOP EM DESEMPENHO DE SISTEMAS COMPUTACIONAIS E DE COMUNICAÇÃO (WPERFORMANCE), 11. , 2012, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2012
.
p. 99-112.
ISSN 2595-6167.
