Differentially private spectrum auction with approximate revenue maximization

Zhu, Ruihao; Li, Zhijing; Wu, Fan; Shin, Kang G.; Chen, Guihai

doi:10.1145/2632951.2632974

Cited by 54 publications

(34 citation statements)

References 34 publications

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“…, r iK ). In existing works [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], K=1 and the interference status between any two bidders is modeled in a binary manner: "yes" (i.e., cannot simultaneously share a band) or "no" (i.e., can simultaneously share). To ease the exposition when K is large, we assume each bidder has two options for its requested coverages (i.e., K=2).…”

Section: B Problem Modelmentioning

confidence: 99%

“…Another significant issue is the privacy, for example, Li et al in [5] presented PPER to protect users' bid privacy but the bidders are terminal user pairs rather than base stations. DEAR in [9] achieves approximate truthfulness, privacy preservation. However, the bidders are assumed to be distributed in homogeneous conventional hexagons, while in future spectrum market, base stations from different MNOs are heterogeneous and arbitrarily distributed.…”

Section: Related Workmentioning

confidence: 99%

“…Note that existing auction-based spectrum sharing schemes (e.g., [5] [6] [7] [8] [9] [10]) often only considered bidders' payment. In such cases, single-attribute auctions were often recruited and proved to be an efficient tool (with regards to both economic-and operation-robustness).…”

mentioning

confidence: 99%

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Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework

Wang

Nguyen

Dutkiewicz

et al. 2017

IEEE Trans. Cogn. Commun. Netw.

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Abstract-Auction-based spectrum sharing is a promising solution to improve the spectrum utilization in 5G networks. Along with the spatial reuse, we observe that the ability to adjust the coverage of a spectrum bidder can provide room to itself for further negotiation while auctioning. In this work, we propose a novel economic tool, Size-Negotiable Auction Mechanism (SNAM), which provides a hybrid solution between auction and negotiation for multi-buyers sharing spectrum chunks from a common database. Unlike existing auction-based spectrum sharing models, each bidder of the SNAM submits its bid for using the spectrum per unit space and a set of coverage ranges over which the bidder is willing to pay for the spectrum. The auctioneer then coordinates the interference areas (or coverage negotiation) to ensure no two winners interfere with each other while aiming to maximize the auction's total coverage area or revenue. In this scenario, the undirected graph used by existing auction mechanisms fails to model the interference among bidders. Instead, we construct a mixed interference graph and prove that SNAM's auctioning on the mixed graph is truthful and individually rational. Simulation results show that, compared with existing auction approaches, the proposed SNAM dramatically improves the spatial efficiency, hence leads to significantly higher seller revenue and buyer satisfaction under various setups. Thanks to its low complexity and low overhead, SNAM can target fine timescale trading (in minutes or hours) with a large number of bidders and requested coverages.

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Section: B Problem Modelmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework

Wang

Nguyen

Dutkiewicz

et al. 2017

IEEE Trans. Cogn. Commun. Netw.

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“…Furthermore, PISA protects both bid privacy and coverage/interference area privacy. Recently, Zhu et al [44], [45] extended the exponential mechanism in [20] and proposed the first differentially privacy-preserving spectrum auction with approximate revenue maximization, under the assumption that the auctioneer is trustworthy. However, as mentioned before, bidders are reluctant to share their bidding information with anyone else, including the auctioneer.…”

Section: B Dynamic Spectrum Auctionmentioning

confidence: 99%

A General Privacy-Preserving Auction Mechanism for Secondary Spectrum Markets

Huang

Gui

et al. 2016

IEEE/ACM Trans. Networking

Self Cite

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Auctions are among the best-known market-based tools to solve the problem of dynamic spectrum redistribution. In recent years, a good number of strategy-proof auction mechanisms have been proposed to improve spectrum utilization and to prevent market manipulation. However, the issue of privacy preservation in spectrum auctions remains open. On the one hand, truthful bidding reveals bidders' private valuations of the spectrum. On the other hand, coverage/interference areas of the bidders may be revealed to determine conflicts. In this paper, we present PISA, which is a PrIvacy preserving and Strategy-proof Auction mechanism for spectrum allocation. PISA provides protection for both bid privacy and coverage/interference area privacy leveraging a privacy-preserving integer comparison protocol, which is well applicable in other contexts. We not only theoretically prove the privacy-preserving properties of PISA, but also extensively evaluate its performance. Evaluation results show that PISA achieves good spectrum allocation efficiency with light computation and communication overheads.Index Terms-Mechanism design, privacy preservation, radio spectrum management.

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“…Moreover, the current research works and literatures have studied revenue maximization auction [5], truthfulness guaranty auction [6][7][8], flexible auction [9], and so on. Spectrum auction has been widely discussed in literature [10,11].…”

Section: Introductionmentioning

confidence: 99%

Stackelberg game-based precoding and power allocation for spectrum auction in fractional frequency reuse cognitive cellular systems

Zhao

Nie

Chen

2016

J Wireless Com Network

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Spectrum auction has been considered as a promising approach to effectively reallocate spectrum resources in the secondary spectrum market. In our previous work, spectrum auction in a fractional frequency reuse (FFR) cognitive cellular system was studied. However, the bidding and valuation model of secondary users (SUs) are not close to practical applications as they introduced a random value of a fixed scope. In this paper, through an optimal interference price announced by the primary user (PU), a joint precoding and power allocation algorithm via Stackelberg game (OIPPS) is proposed to improve the spectrum auction problem subject to the interference constraint of PU, the transmission power constraint of SUs, and the signal-to-interference-plus-noise ratio (SINR) constraint of each SU in the FFR cognitive cellular system. Simulation results show the effectiveness of the proposed OIPPS algorithm in terms of the convergence of precoding and power allocation vectors and the maximized sum utility of SUs while taking full consideration of the PU's revenue. Besides, a comparison between the bidding improved spectrum auction scheme and a traditional method is proposed to show the effectiveness of our proposed algorithm.

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Differentially private spectrum auction with approximate revenue maximization

Cited by 54 publications

References 34 publications

Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework

Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework

A General Privacy-Preserving Auction Mechanism for Secondary Spectrum Markets

Stackelberg game-based precoding and power allocation for spectrum auction in fractional frequency reuse cognitive cellular systems

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