Abstract
Cooperative cognitive radio networks have been proposed to address spectrum starvation problem and enhance the transmission rate of mobile devices. Most works assume one user could afford the whole spectrum and neglect the selfishness nature, which is not practical. Based on group-buying, a two-stage auction mechanism named TAMSA is proposed to guarantee the quality of service and improve the utilization ratio of spectrum resources. TAMSA is an incentive mechanism involving the primary users (PUs) and relay nodes. TAMSA can also reduce the cost of the secondary users (SUs) and increase utilities for both PUs and relay nodes. In the first stage, SUs submit their budgets, valuations and demands for spectrum resources to relay nodes in group-buying, relay nodes calculate revenues and determine the winning SUs. In the second stage, we execute VCG auction between the relay nodes and PUs, with a maximum-weighted-matching algorithm. TAMSA can effectively allocate spectrum resources to meet the demands of SUs. We show that TAMSA is truthful, individual rational and computational efficient. Extensive simulation results show that TAMSA outperforms random algorithm by 256% in terms of average utility of PUs. TAMSA is able to improve the average utility of SUs and relay nodes significantly up to 213% and 10 times respectively. TAMSA is further improved by 28.33% and 78.65% in terms of average utility of PUs over TASG and TACC, respectively.
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References
Zheng, Z., Wu, F., Tang, S., et al.: AEGIS: an unknown combinatorial auction mechanism framework for heterogeneous spectrum redistribution in noncooperative wireless networks. IEEE/ACM Trans. Netw. 24(3), 1919–1932 (2016)
Zhu, Y., Li, B., Li, Z., et al.: Truthful spectrum auction design for secondary networks. In: INFOCOM, pp. 873–881. IEEE, Orlando, FL, USA (2012)
Chen, L., Huang, L., Xu, H., et al.: Optimal channel allocation for multi-PU and multi-SU pairs in underlay cognitive radio networks. Int. J. Ad Hoc Ubiquitous Comput. 27(1), 19–33 (2018)
Wang, X., Huang, L., Xu, H., et al.: Truthful auction for resource allocation in cooperative cognitive radio networks. In: 24th International Conference on Computer Communication and Networks, pp. 1–8. IEEE, Las Vegas, NV, USA (2015)
Wang, X., Huang, L., Xu, H., et al.: Social welfare maximization auction for secondary spectrum markets: a long-term perspective. In: 13th IEEE International Conference on Sensing, Communication, and Networking, Communication, and Networking, pp. 1–9. IEEE, London, UK (2016)
Shen, F., Li, D., Lin, P.H., et al.: Auction based spectrum sharing for hybrid access in macro-femtocell networks under QoS requirements. In: IEEE International Conference on Communications, pp. 3335–3340. IEEE, London, UK (2015)
Wang, H., Liu, Z., Cheng, Z., et al.: Maximization of link capacity by joint power and spectrum allocation for smart satellite transponder. In: 23rd Asia-Pacific Conference on Communications, pp. 1–6. IEEE, Perth, WA, Australia (2017)
Jia, J., Zhang, Q., Zhang, Q., et al.: Revenue generation for truthful spectrum auction in dynamic spectrum access. In: 10th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 3–12. ACM, New Orleans, Louisiana, USA (2009)
Liu, Y., Tao, M., Huang, J.: An auction approach to distributed power allocation for multiuser cooperative networks. IEEE Trans. Wirel. Commun. 12(1), 237–247 (2012)
Shi, W., Zhang, L., Wu, C., et al.: An online auction framework for dynamic resource provisioning in cloud computing. IEEE-ACM Trans. Netw. 24(4), 2060–2073 (2016)
Feng, Z., Zhu, Y., Zhang, Q., et al.: TRAC: truthful auction for location-aware collaborative sensing in mobile crowdsourcing. In: INFOCOM, pp. 1231–1239. IEEE, Toronto, ON, Canada (2014)
Wu, F., Vaidya, N.: A strategy-proof radio spectrum auction mechanism in noncooperative wireless networks. IEEE Trans. Mob. Comput. 12(5), 885–894 (2013)
Lee, C., Wang, P., Niyato, D.: A real-time group auction system for efficient allocation of cloud internet applications. IEEE Trans. Serv. Comput. 8(2), 251–268 (2015)
Lin, P., et al.: Groupon in the Air: A three-stage auction framework for Spectrum Group-buying. In: INFOCOM, pp. 2013–2021. IEEE, Turin, Italy (2013)
Advaita, A., Gali, M.M., Chu, T.M.C., et al.: Outage probability of MIMO cognitive cooperative radio networks with multiple AF relays using orthogonal space-time block codes. In: Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 84–89. IEEE, Rome, Italy (2017)
Yang, D., Xue, G., Zhang, X.: Group buying spectrum auctions in cognitive radio networks. IEEE Trans. Veh. Technol. 66(1), 810–817 (2017)
Yang, D., Fang, X., Xue, G.: Truthful auction for cooperative communications. In: IEEE International Conference on Communications, pp. 1–10. IEEE, Ottawa, ON, Canada (2011)
Chen, L., Wu, J., Zhang, X.X., et al.: TARCO: two-stage auction for D2D relay aided computation resource allocation in HetNet. IEEE Trans. Serv. Comput. PP(99), 1 (2017)
Acknowledgment
This work was supported by the National Natural Science Foundation of China under Grant Nos. 61702115 and 61672171, Natural Science Foundation of Guangdong, China under Grant No. 2018B030311007, and Major R&D Project of Educational Commission of Guangdong under Grant No. 2016KZDXM052. This work was also supported by China Postdoctoral Science Foundation Fund under Grant No. 2017M622632.
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Zhang, X., Wu, J., Chen, L. (2018). TAMSA: Two-Stage Auction Mechanism for Spectrum Allocation in Cooperative Cognitive Radio Networks. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_1
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DOI: https://doi.org/10.1007/978-3-030-05057-3_1
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