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Publisher: Institute of Electrical and Electronics Engineers
Languages: English
Types: Unknown
Dynamic Spectrum Sharing (DSS) aims to provide opportunistic access to under-utilised spectrum in cellular networks for secondary network operators. In this paper we propose an algorithm using stochastic and optimisation models to borrow spectrum bandwidths under the assumption that more resources exist for secondary access than the secondary network demand by considering a merchant mode. The main aim of the paper is to address the problem of spectrum borrowing in DSS environments, where a secondary network operator aims to borrow the required spectrum from multiple primary network operators to achieve a maximum profit under specific grade of service (GoS) and budget restriction. We assume that the primary network operators offer spectrum access opportunities with variable number of channels (contiguous and/or non-contiguous) at variable prices. Results obtained are then compared with results derived from an algorithm in which spectrum borrowing are random. Comparisons showed that the gain in the results obtained from our proposed stochastic-optimisation framework is significantly higher than random counterpart.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] M. Matinmikko, H. Okkonen, M. Palola, S. Yrjola, P. Ahokangas, and M. Mustonen, “Spectrum sharing using licensed shared access: the concept and its workflow for lte-advanced networks,” IEEE Wireless Communications, vol. 21, no. 2, pp. 72-79, 2014.
    • [2] A. Palaios, J. Riihijarvi, P. Mahonen, V. Atanasovski, L. Gavrilovska, P. Van Wesemael, A. Dejonghe, and P. Scheele, “Two days of spectrum use in europe,” in 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2012, pp. 24-29.
    • [3] M. M. Buddhikot, P. Kolodzy, S. Miller, K. Ryan, and J. Evans, “Dimsumnet: new directions in wireless networking using coordinated dynamic spectrum,” in Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks. Ieee, 2005, pp. 78-85.
    • [4] M. M. Buddhikot and K. Ryan, “Spectrum management in coordinated dynamic spectrum access based cellular networks,” in New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005. 2005 First IEEE International Symposium on. IEEE, 2005, pp. 299-307.
    • [5] M. M. Buddhikot, I. Kennedy, F. Mullany, and H. Viswanathan, “Ultrabroadband femtocells via opportunistic reuse of multi-operator and multi-service spectrum,” Bell Labs Technical Journal, vol. 13, no. 4, pp. 129-143, 2009.
    • [6] OfCom, “Application of spectrum liberalisation and trading to the mobile sector - A further consultation,” http://stakeholders.ofcom.org.uk/binaries/consultations/spectrumlib/anne xes/annex10.pdf, The Office of Communications, Tech. Rep., 2009.
    • [7] S. Li, J. Huang, and S.-Y. R. Li, “Dynamic profit maximization of cognitive mobile virtual network operator,” IEEE Transactions on Mobile Computing, vol. 13, no. 3, pp. 526-540, 2014.
    • [8] V. Sridhar and R. Prasad, “Towards a new policy framework for spectrum management in india,” Telecommunications Policy, vol. 35, no. 2, pp. 172-184, 2011.
    • [9] A. Bourdena, E. Pallis, G. Kormentzas, and G. Mastorakis, “A prototype cognitive radio architecture for tvws exploitation under the real time secondary spectrum market policy,” Physical Communication, vol. 10, pp. 159-168, 2014.
    • [10] J. Lunden, V. Koivunen, and H. V. Poor, “Spectrum exploration and exploitation for cognitive radio: Recent advances,” IEEE Signal Processing Magazine, vol. 32, no. 3, pp. 123-140, 2015.
    • [11] F. Akhtar, M. H. Rehmani, and M. Reisslein, “White space: Definitional perspectives and their role in exploiting spectrum opportunities,” Telecommunications Policy, vol. 40, no. 4, pp. 319-331, 2016.
    • [12] C. Jiang, Y. Chen, K. R. Liu, and Y. Ren, “Optimal pricing strategy for operators in cognitive femtocell networks,” IEEE Transactions on Wireless Communications, vol. 13, no. 9, pp. 5288-5301, 2014.
    • [13] D. S. Palguna, D. J. Love, and I. Pollak, “Secondary spectrum auctions for markets with communication constraints,” IEEE Transactions on Wireless Communications, vol. 15, no. 1, pp. 116-130, 2016.
    • [14] H. Zhang, C. Jiang, X. Mao, and H.-H. Chen, “Interference-limited resource optimization in cognitive femtocells with fairness and imperfect spectrum sensing,” IEEE Transactions on Vehicular Technology, vol. 65, no. 3, pp. 1761-1771, 2016.
    • [15] A. Afana, V. Asghari, A. Ghrayeb, and S. Affes, “On the performance of cooperative relaying spectrum-sharing systems with collaborative distributed beamforming,” IEEE Transactions on Communications, vol. 62, no. 3, pp. 857-871, 2014.
    • [16] L. Wei, R. Q. Hu, Y. Qian, and G. Wu, “Energy efficiency and spectrum efficiency of multihop device-to-device communications underlaying cellular networks,” IEEE Transactions on Vehicular Technology, vol. 65, no. 1, pp. 367-380, 2016.
    • 10 20 30 40 60 70 80 90 100 10 20 30 70 80 90 100 itf40 o r 30 P 3000 d e iruq2500 c a lse2000 n n a fch1500 o r e bm1000 u N 500 00 10 20 30 40 50 60 Number of cells 70 80 90 100
    • [17] Y. Zhang, C. Lee, D. Niyato, and P. Wang, “Auction approaches for resource allocation in wireless systems: A survey,” IEEE Communications Surveys & Tutorials, vol. 15, no. 3, pp. 1020-1041, 2013.
    • [18] C. A. Gizelis and D. D. Vergados, “A survey of pricing schemes in wireless networks,” IEEE Communications Surveys & Tutorials, vol. 13, no. 1, pp. 126-145, 2011.
    • [19] X. Kang, R. Zhang, and M. Motani, “Price-based resource allocation for spectrum-sharing femtocell networks: A stackelberg game approach,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 3, pp. 538-549, 2012.
    • [20] A.-H. Mohsenian-Rad, V. W. Wong, and V. Leung, “Two-fold pricing to guarantee individual profits and maximum social welfare in multi-hop wireless access networks,” IEEE Transactions on Wireless Communications, vol. 8, no. 8, pp. 4110-4121, 2009.
    • [21] N. Tran, L. B. Le, S. Ren, Z. Han, and C. S. Hong, “Joint pricing and load balancing for cognitive spectrum access: Non-cooperation versus cooperation,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 5, pp. 972-985, May 2015.
    • [22] R. Abozariba, M. Asaduzzaman, and M. Patwary, “Radio resource sharing framework for cooperative multi-operator networks with dynamic overflow modelling,” IEEE Transactions on Vehicular Technology, 2016, In press.
    • [23] J. W. Mwangoka, P. Marques, and J. Rodriguez, “Broker based secondary spectrum trading,” in Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2011 Sixth International ICST Conference on. IEEE, 2011, pp. 186-190.
    • [24] S. Sengupta and M. Chatterjee, “An economic framework for dynamic spectrum access and service pricing,” IEEE/ACM Transactions on Networking (TON), vol. 17, no. 4, pp. 1200-1213, 2009.
    • [25] M. Khaledi and A. A. Abouzeid, “Dynamic spectrum sharing auction with time-evolving channel qualities,” IEEE Transactions on Wireless Communications, vol. 14, no. 11, pp. 5900-5912, 2015.
    • [26] Y. Wu, Q. Zhu, J. Huang, and D. H. Tsang, “Revenue sharing based resource allocation for dynamic spectrum access networks,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 11, pp. 2280-2296, 2014.
    • [27] I. Sugathapala, I. Kovacevic, B. Lorenzo, S. Glisic, and Y. M. Fang, “Quantifying benefits in a business portfolio for multi-operator spectrum sharing,” IEEE Transactions on Wireless Communications, vol. 14, no. 12, pp. 6635-6649, 2015.
    • [28] Y. Song, C. Zhang, Y. Fang, and P. Lin, “Revenue maximization in time-varying multi-hop wireless networks: A dynamic pricing approach,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 7, pp. 1237-1245, 2012.
    • [29] L. Gao, J. Huang, Y.-J. Chen, and B. Shou, “An integrated contract and auction design for secondary spectrum trading,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 3, pp. 581-592, 2013.
    • [30] D. Niyato and E. Hossain, “Competitive pricing for spectrum sharing in cognitive radio networks: Dynamic game, inefficiency of nash equilibrium, and collusion,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 192-202, 2008.
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