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Integrating Two Feedback Queuing Discipline into Cognitive Radio Channel Aggregation

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Języki publikacji
EN
Abstrakty
EN
Queuing regime is one outstanding approach in improving channel aggregation. If well designed and incorporated with carefully selected parameters, it enhances the smooth rollout of fifth/next generation wireless networks. While channel aggregation is the merging of scattered TV white space (spectrum holes) into one usable chunk for secondary users (SU). The queuing regime ensures that these unlicensed users (SUs) traffic/services are not interrupted permanently (blocked/dropped or forced to terminate) in the event of the licensed users (primary user) arrival. However, SUs are not identical in terms of traffic class and bandwidth consumption hence, they are classified as real time and non-real time SU respectively. Several of these strategies have been studied considering queuing regime with a single feedback queuing discipline. In furtherance to previous proposed work with single feedback queuing regime, this paper proposes, develops and compares channel aggregation policies with two feedback queuing regimes for the different classes of SUs. The investigation aims at identifying the impacts of the twofeedback queuing regime on the performance of the secondary network such that any SU that has not completed its ongoing service are queued in their respective buffers. The performance is evaluated through a simulation framework. The results validate that with a well-designed queuing regime, capacity, access and other indices are improved with significant decrease in blocking and forced termination probabilities respectively.
Twórcy
autor
  • Centre for Telecommunication, Dept. of Electrical and Electronic Engineering Science, University of Johannesburg. P. O. Box 524, Auckland Park, 2006, South Africa
autor
  • Centre for Telecommunication, Dept. of Electrical and Electronic Engineering Science, University of Johannesburg. P. O. Box 524, Auckland Park, 2006, South Africa
  • Centre for Telecommunication, Dept. of Electrical and Electronic Engineering Science, University of Johannesburg. P. O. Box 524, Auckland Park, 2006, South Africa
Bibliografia
  • [1] Y. Liang, K. Cheng, G. Ye. Li, and P. Mahonen, “Cognitive radio network and communication: an overview,” IEEE Transactions on Vehicular Technology, vol. 60, no. 7, pp. 3386-3407, Sept. 2011.
  • [2] A. Domenico, E. C. Strinati, and M. G. Benedetto, “Survey on MAC strategies for cognitive radio network,” IEEE Communication Survey and Tutorials, vol. 14, no. 1, pp. 21-43, 2012.
  • [3] V. T. Nguyen, F. Villain, and Y. L. Guillou, “Cognitive radio RF: overview and challenges,” VLSI Design, vol. 2012, pp. 1-13, Feb. 2012.
  • [4] H. Su and X. Zhang, “Cross-layer based opportunistic MAC protocol for QoS providing over cognitive radio wireless networks,” IEEE Journal on Selected Area in Communication, vol. 26, no. 1, pp. 118-129, Jan. 2008.
  • [5] L. Jiao, F. Y. Li, and V. Pla, “Modelling and performance analysis of channel assembling in multi-channel cognitive radio networks with spectrum adaptation,” IEEE Transactions on Vehicular Technology, vol. 61, no. 6, p. 26862697, Jul. 2012.
  • [6] L. Jiao, E. Song, V. Pla, and F. Y. Li, “Capacity upper bound of channel assembling in cognitive radio networks with quasi-stationary primary user activities,” IEEE Transactions on Vehicular Technology, vol. 62, no. 4, pp. 1849-1855, May 2013.
  • [7] I. A. M. Balapuwaduge, L. Jiao, V. Pla, and F. Y. Li, “Channel assembling with priority-based queue in cognitive radio network: strategy and performance,” IEEE Transaction on wireless Communication, vol. 13, no. 2, pp. 630-645, Feb. 2014.
  • [8] E. Esonogho and T. Walingo, “Performance evaluation of channel assembling strategies with multi-class secondary users in cognitive radio networks,” Southern Africa Telecommunication, Networking and Application Conference, Cape Town, South Africa, Sept. 6-9, 2015, pp. 81-86.
  • [9] E. Esenogho and T. Walingo, “evaluation of channel assembling strategies with single-class secondary users in cognitive radio networks,” IEEE Wireless Vitae, Hyderabad, India, Dec. 13-16, 2015.
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  • [11] L. Li, S. Zhang, K. Wang, and W. Zhou, “Queuing method in combined channel assembling and fragmentation strategy for dynamic spectrum access,” IEEE Symposium on personal, Indoor, and Mobile Radio Communication, Sydney, Australia, Sept. 9-12, 2012, pp. 1214-1219.
  • [12] L. Jiao, F. Y. Li, and V. Pla, “Greedy versus dynamic channel assembling strategy in CRNs: Markov models and performance evaluation,” International Networking Conference, Valencia, Spain, May 9-13, 2011, pp. 22-31.
  • [13] L. Jiao, F. Y. Li, and V. Pla, “Analysis on channel bonding/assembling for multi-channel cognitive radio networks,” IEEE European Wireless Conference, Lucca, Italy, Apr. 12-15, 2010, pp. 468-474.
  • [14] X. Wang, Q. Liu, and G. B. Giannakis, “Analyzing and optimizing adaptive modulation coding jointly with ARQ for QoS-guaranteed Traffic,” IEEE Transactions On Vehicular Technology, vol. 56, no. 2, pp. 710-720, Mar. 2007.
  • [15] J. Razavilar, K. J. R. Liu, and S. I. Marcus,, “Jointly optimized bitrate/delay control policy for wireless packet networks with fading channels,” IEEE Transactions on Communication, vol. 50, no. 3, pp. 484494, Mar. 2002.
  • [16] V. B. Iversen, “Teletraffic engineering and network planning”, Technical University of Denmark, 2011. [Online]. Available: http://oldwww.com.dtu.dk/education/34340/telenook.pdf [Accessed 22 January 2016].
  • [17] G. Bolch, S. Greiner, H. de Meer and K. S. Trivedi, “Queuing networks and Markow chains: modelling and performance evaluation with computer science applications”, Wiley-Interscience, May 2006.
Uwagi
1. This work is supported by Centre for telecommunication (CfT) under the Global Excellence Stature Post-Doctoral Research Fellowship program at the University of Johannesburg, South Africa.
2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
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