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research-article

A Truthful Online Incentive Mechanism for Nondeterministic Spectrum Allocation

Authors:

Jianfeng MaAuthors Info & Claims

IEEE Transactions on Wireless Communications, Volume 19, Issue 7

Pages 4632 - 4642

https://doi.org/10.1109/TWC.2020.2985690

Published: 01 July 2020 Publication History

Abstract

Dynamic spectrum access (DSA) is a promising platform to solve the problem of spectrum shortage for which the most challenging issue is spectrum allocation under uncertain availability information, which is referred as a nondeterministic spectrum allocation problem. The nature of such a problem is due to inaccurate spectrum sensing results, which are induced by that power or energy based sensing can be greatly impacted by thermal and environmental noise. For spectrum allocation, auction-based mechanisms have been extensively studied because of channel allocation efficiency, and its potential to achieve bidding truthfulness for secondary uses (SUs). However, most existing spectrum auction mechanisms focus on realizing the truthfulness under certain spectrum availability information. In this paper, we propose FORTUNE, the first truthful online auction mechanism for nondeterministic spectrum allocation by considering uncertain spectrum availability and dynamic spectrum requests. Specifically, we take limited information to compute expected income and losses when interference between primary users (PUs) and SUs occurs, and present a virtual request method for changing of spectrum’s actual state. Thorough theoretical analysis proves the truthfulness of FORTUNE. Furthermore, given a sample set with 5%-30% noise in spectrum sensing, FORTUNE achieves not only truthfulness, but also up to 50% higher channel utilization than existing spectrum auction mechanisms.

References

[1]

Ridhima and A. Singh Buttar, “Fundamental operations of cognitive radio: A survey,” in Proc. IEEE Int. Conf. Electr., Comput. Commun. Technol. (ICECCT), Feb. 2019, pp. 1–5.

[2]

F. Wu, Q. Huang, Y. Tao, and G. Chen, “Towards privacy preservation in strategy-proof spectrum auction mechanisms for noncooperative wireless networks,” IEEE/ACM Trans. Netw., vol. 23, no. 4, pp. 1271–1285, Aug. 2015.

Digital Library

[3]

Y. Chen, P. Lin, and Q. Zhang, “LOTUS: location-aware online truthful double auction for dynamic spectrum access,” IEEE Trans. Wireless Commun., vol. 14, no. 2, pp. 1092–1099, Feb. 2015.

[4]

S. Wang, P. Xu, X. Xu, S. Tang, X. Li, and X. Liu, “TODA: Truthful online double auction for spectrum allocation in wireless networks,” in Proc. IEEE Symp. New Frontiers Dyn. Spectr. (DySPAN), Apr. 2010, pp. 1–10.

[5]

Q. Wanget al., “Robust large-scale spectrum auctions against false-name bids,” IEEE Trans. Mobile Comput., vol. 16, no. 6, pp. 1730–1743, Jun. 2017.

Digital Library

[6]

T. Sanguanpuak, S. Guruacharya, N. Rajatheva, M. Bennis, and M. Latva-Aho, “Multi-operator spectrum sharing for small cell networks: A matching game perspective,” IEEE Trans. Wireless Commun., vol. 16, no. 6, pp. 3761–3774, Jun. 2017.

[7]

M. Lopez-Benitez and F. Casadevall, “Signal uncertainty in spectrum sensing for cognitive radio,” IEEE Trans. Commun., vol. 61, no. 4, pp. 1231–1241, Apr. 2013.

[8]

F. Z. El Bahi, H. Ghennioui, and M. Zouak, “Spectrum sensing technique of OFDM signal under noise uncertainty based on mean ambiguity function for cognitive radio,” Phys. Commun., vol. 33, pp. 142–150, Apr. 2019.

Digital Library

[9]

O. H. Toma, M. Lopez-Benitez, D. K. Patel, and K. Umebayashi, “Estimation of primary channel activity statistics in cognitive radio based on imperfect spectrum sensing,” IEEE Trans. Commun., pp. 1–1, 2020.

[10]

D. Roy, T. Mukherjee, M. Chatterjee, and E. Pasiliao, “Primary user activity prediction in DSA networks using recurrent structures,” in Proc. IEEE Int. Symp. Dyn. Spectr. Access Netw. (DySPAN), Nov. 2019, pp. 1–10.

[11]

Q. Huang, Y. Gui, F. Wu, G. Chen, and Q. Zhang, “A general privacy-preserving auction mechanism for secondary spectrum markets,” IEEE/ACM Trans. Netw., vol. 24, no. 3, pp. 1881–1893, Jun. 2016.

Digital Library

[12]

Q. Huang, Y. Tao, and F. Wu, “SPRING: A strategy-proof and privacy preserving spectrum auction mechanism,” in Proc. IEEE INFOCOM, Apr. 2013, pp. 827–835.

[13]

X. Zhou and H. Zheng, “TRUST: A general framework for truthful double spectrum auctions,” in Proc. IEEE 28th Conf. Comput. Commun. (INFOCOM), Apr. 2009, pp. 999–1007.

[14]

Z. Chen, L. Huang, and L. Chen, “ITSEC: An information-theoretically secure framework for truthful spectrum auctions,” in Proc. IEEE Conf. Comput. Commun. (INFOCOM), Apr. 2015, pp. 2065–2073.

[15]

Z. Chenet al., “PS-TRUST: Provably secure solution for truthful double spectrum auctions,” in Proc. IEEE Conf. Comput. Commun. (INFOCOM), Apr. 2014, pp. 1249–1257.

[16]

D. Yang, X. Zhang, and G. Xue, “PROMISE: A framework for truthful and profit maximizing spectrum double auctions,” in Proc. IEEE Conf. Comput. Commun. (INFOCOM), Apr. 2014, pp. 109–117.

[17]

M. Dong, G. Sun, X. Wang, and Q. Zhang, “Combinatorial auction with time-frequency flexibility in cognitive radio networks,” in Proc. IEEE INFOCOM, Mar. 2012, pp. 2282–2290.

[18]

R. Zhu and K. G. Shin, “Differentially private and strategy-proof spectrum auction with approximate revenue maximization,” in Proc. IEEE Conf. Comput. Commun. (INFOCOM), Apr. 2015, pp. 918–926.

[19]

P. Xu and X.-Y. Li, “TOFU: semi-truthful online frequency allocation mechanism for wireless networks,” IEEE/ACM Trans. Netw., vol. 19, no. 2, pp. 433–446, Apr. 2011.

Digital Library

[20]

P. Xu, X. Xu, S. Tang, and X.-Y. Li, “Truthful online spectrum allocation and auction in multi-channel wireless networks,” in Proc. IEEE INFOCOM, Apr. 2011, pp. 26–30.

[21]

V. S. S. Nadendla, S. K. Brahma, and P. K. Varshney, “Optimal spectrum auction design with 2-D truthful revelations under uncertain spectrum availability,” IEEE/ACM Trans. Netw., vol. 25, no. 1, pp. 420–433, Feb. 2017.

Digital Library

[22]

Y. Chen, X. Tian, Q. Wang, M. Li, M. Du, and Q. Li, “ARMOR: A secure combinatorial auction for heterogeneous spectrum,” IEEE Trans. Mobile Comput., vol. 18, no. 10, pp. 2270–2284, Oct. 2019.

[23]

X. Dong, Q. Kang, Y. Xu, Z. Ma, and T. Li, “Poster abstract: A practical Sybil-proof incentive mechanism for multichannel allocation,” in Proc. IEEE Conf. Comput. Commun. Workshops (INFOCOM WKSHPS), Apr. 2019, pp. 1047–1048.

[24]

X. Zhou, S. Gandhi, S. Suri, and H. Zheng, “EBay in the sky: Strategy-proof wireless spectrum auctions,” in Proc. 14th ACM Int. Conf. Mobile Comput. Netw. (MobiCom), 2008, pp. 2–13.

[25]

Z. Zheng, F. Wu, and G. Chen, “A strategy-proof combinatorial heterogeneous channel auction framework in noncooperative wireless networks,” IEEE Trans. Mobile Comput., vol. 14, no. 6, pp. 1123–1137, Jun. 2015.

[26]

X. Wang, Y. Ji, H. Zhou, Z. Liu, Y. Gu, and J. Li, “A privacy preserving truthful spectrum auction scheme using homomorphic encryption,” in Proc. IEEE Global Commun. Conf. (GLOBECOM), Dec. 2015, pp. 1–6.

[27]

P. Xu, X.-Y. Li, and S. Tang, “Efficient and strategyproof spectrum allocations in multichannel wireless networks,” IEEE Trans. Comput., vol. 60, no. 4, pp. 580–593, Apr. 2011.

Digital Library

[28]

F. Wu and N. Vaidya, “A strategy-proof radio spectrum auction mechanism in noncooperative wireless networks,” IEEE Trans. Mobile Comput., vol. 12, no. 5, pp. 885–894, May 2013.

Digital Library

[29]

M. Al-Ayyoub and H. Gupta, “Truthful spectrum auctions with approximate revenue,” in Proc. IEEE INFOCOM, Apr. 2011, pp. 2813–2821.

[30]

J. Jia, Q. Zhang, Q. Zhang, and M. Liu, “Revenue generation for truthful spectrum auction in dynamic spectrum access,” in Proc. 10th ACM Int. Symp. Mobile Ad Hoc Netw. Comput. (MobiHoc), 2009, pp. 3–12.

[31]

X. Dong, Y. Gong, J. Ma, and Y. Guo, “Protecting operation-time privacy of primary users in downlink cognitive two-tier networks,” IEEE Trans. Veh. Technol., vol. 67, no. 7, pp. 6561–6572, Jul. 2018.

[32]

X. Dong, T. Zhang, D. Lu, G. Li, Y. Shen, and J. Ma, “Preserving geo-indistinguishability of the primary user in dynamic spectrum sharing,” IEEE Trans. Veh. Technol., vol. 68, no. 9, pp. 8881–8892, Sep. 2019.

[33]

Q. Wang, Q. Sun, K. Ren, and X. Jia, “THEMIS: Collusion-resistant and fair pricing spectrum auction under dynamic supply,” IEEE Trans. Mobile Comput., vol. 16, no. 7, pp. 2051–2064, Jul. 2017.

[34]

S. Li, Z. Zheng, E. Ekici, and N. B. Shroff, “Maximizing social welfare in operator-based cognitive radio networks under spectrum uncertainty and sensing inaccuracy,” in Proc. IEEE INFOCOM, Apr. 2013, pp. 953–961.

[35]

E. Axell, G. Leus, E. Larsson, and H. Poor, “Spectrum sensing for cognitive radio: State-of-the-Art and recent advances,” IEEE Signal Process. Mag., vol. 29, no. 3, pp. 101–116, May 2012.

[36]

M. Cheng, X. Gong, and L. Cai, “Joint routing and link rate allocation under bandwidth and energy constraints in sensor networks,” IEEE Trans. Wireless Commun., vol. 8, no. 7, pp. 3770–3779, Jul. 2009.

Digital Library

[37]

R. Jain, D. Chiu, and W. Hawe, “A quantitative measure of fairness and discrimination for resource allocation in shared computer systems,” DEC Res., Palo Alto, CA, USA, Tech. Rep., 1984.

Cited By

Qi NHuang ZSun WJin SSu X(2023)Coalitional Formation-Based Group-Buying for UAV-Enabled Data Collection: An Auction Game ApproachIEEE Transactions on Mobile Computing10.1109/TMC.2022.321144722:12(7420-7437)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1109/TMC.2022.3211447

Index Terms

A Truthful Online Incentive Mechanism for Nondeterministic Spectrum Allocation
1. Networks
  1. Network services
  2. Network types
2. Theory of computation
  1. Theory and algorithms for application domains

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Wireless Communications

IEEE Transactions on Wireless Communications Volume 19, Issue 7

July 2020

720 pages

ISSN:1536-1276

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1536-1276 © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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Published: 01 July 2020

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Cited By

Qi NHuang ZSun WJin SSu X(2023)Coalitional Formation-Based Group-Buying for UAV-Enabled Data Collection: An Auction Game ApproachIEEE Transactions on Mobile Computing10.1109/TMC.2022.321144722:12(7420-7437)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1109/TMC.2022.3211447

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