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1. Spot Markets for Spectrum Measurements

   https://doi.org/10.1109/DySPAN.2019.8935666  

   Ghosh, Arnob ; Berry, Randall ( November 2019 , IEEE DySPAN)

   The recent framework for spectrum sharing in the 3.5 GHz band allows for Environment Sensing Capability operators (ESCs) to measure spectrum occupancy so as to enable commercial use of this spectrum when federal incumbent users are not present. Each ESC will contract with one or more Spectrum Access Systems (SASs) to provide spectrum occupancy data. Commercial firms using the band will in turn contract with a SAS to determine when it can access the spectrum. Initially, the decisions of which ESC and SAS to partner with will likely be based on long-term contracts. In this paper, we consider an alternative framework, in which an ESC sells its spectrum management information via a spot market so that from periodto- period a commercial user can select a different ESC from which to acquire spectrum measurements. We develop a game theoretic model to analyze such a market and show that using such a spot market may better enable multiple commercial firms to operate in a given spectrum band. We also show that this increased competition may not benefit consumer surplus unless firms adopt a non-stationary strategy profile. 

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2. Differentially-Private Incentive Mechanism for Crowdsourced Radio Environment Map Construction

   https://doi.org/10.1109/INFOCOM.2019.8737512  

   Hu, Yidan ; Zhang, Rui ( April 2019 , IEEE INFOCOM 2019 - IEEE Conference on Computer Communications)

   Database-driven Dynamic Spectrum Sharing (DSS) is a promising technical paradigm for enhancing spectrum efficiency by allowing secondary user to opportunistically access licenced spectrum channels without interfering with primary users' transmissions. In database-driven DSS, a geo-location database administrator (DBA) maintains the spectrum availability in its service region in the form of a radio environment map (REM) and grant or deny secondary users' spectrum access requests based on primary users' activities. Crowdsourcing-based spectrum sensing has great potential in improving the accuracy of the REM at the DBA but requires strong incentives and privacy protection to simulate mobile users' participation. To tackle this challenge, this paper introduces a novel differentially-private reverse auction mechanism for crowdsourcing-based spectrum sensing. The proposed mechanism allows the DBA to select spectrum sensing participants under a budget constraint while offering differential bid privacy, approximate truthfulness, and approximate accuracy maximization. Extensive simulation studies using a real spectrum measurement dataset confirm the efficacy and efficiency of the proposed mechanism. 

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3. Differentially-Private Incentive Mechanism for Crowdsourced Radio Environment Map Construction

   Hu, Yidan ; Zhang, Rui ( April 2019 , IEEE International Conference on Computer Communications)

   Database-driven Dynamic Spectrum Sharing (DSS) is a promising technical paradigm for enhancing spectrum efficiency by allowing secondary user to opportunistically access licenced spectrum channels without interfering with primary users' transmissions. In database-driven DSS, a geo-location database administrator (DBA) maintains the spectrum availability in its service region in the form of a radio environment map (REM) and grant or deny secondary users' spectrum access requests based on primary users' activities. Crowdsourcing-based spectrum sensing has great potential in improving the accuracy of the REM at the DBA but requires strong incentives and privacy protection to simulate mobile users' participation. To tackle this challenge, this paper introduces a novel differentially-private reverse auction mechanism for crowdsourcing-based spectrum sensing. The proposed mechanism allows the DBA to select spectrum sensing participants under a budget constraint while offering differential bid privacy, approximate truthfulness, and approximate accuracy maximization. Extensive simulation studies using a real spectrum measurement dataset confirm the efficacy and efficiency of the proposed mechanism. 

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4. A two-sided model of paid peering

   https://doi.org/10.1016/j.telpol.2022.102352  

   Nikkhah, Ali ; Jordan, Scott ( May 2022 , Telecommunications policy)

   Internet users have suffered collateral damage in tussles over paid peering between large ISPs and large content providers. Paid peering is a relationship where two networks exchange traffic with payment, which provides direct access to each other’s customers without having to pay a third party to carry that traffic for them. The issue will arise again when the United States Federal Communications Commission (FCC) considers a new net neutrality order. We first consider the effect of paid peering on broadband prices. We adopt a two-sided market model in which an ISP maximizes profit by setting broadband prices and a paid peering price. We analytically derive the profit-maximizing prices, and show that they satisfy a generalization of the well-known Lerner rule. Our result shows that paid peering fees reduce the premium plan price, increase the video streaming price and the total price for premium tier customers who subscribe to video streaming services; however, the ISP passes on to its customers only a portion of the revenue from paid peering. ISP profit increases but video streaming profit decreases as an ISP moves from settlement-free peering to paid peering price. We next consider the effect of paid peering on consumer surplus. We find that consumer surplus is a uni-modal function of the paid peering fee. The paid peering fee that maximizes consumer surplus depends on elasticities of demand for broadband and for video streaming. However, consumer surplus is maximized when paid peering fees are significantly lower than those that maximize ISP profit. However, it does not follow that settlement-free peering is always the policy that maximizes consumer surplus. The peering price depends critically on the incremental ISP cost per video streaming subscriber; at different costs, it can be negative, zero, or positive. 

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5. Ibex: Privacy-preserving Ad Conversion Tracking and Bidding

   https://doi.org/10.1145/3548606.3560651  

   Zhong, Ke ; Ma, Yiping ; Angel, Sebastian ( November 2022 , AACM SIGSAC Conference on Computer and Communications Security)

   This paper introduces Ibex, an advertising system that reduces the amount of data that is collected on users while still allowing advertisers to bid on real-time ad auctions and measure the effectiveness of their ad campaigns. Specifically, Ibex addresses an issue in recent proposals such as Google’s Privacy Sandbox Topics API in which browsers send information about topics that are of interest to a user to advertisers and demand-side platforms (DSPs). DSPs use this information to (1) determine how much to bid on the auction for a user who is interested in particular topics, and (2) measure how well their ad campaign does for a given audience (i.e., measure conversions). While Topics and related proposals reduce the amount of user information that is exposed, they still reveal user preferences. In Ibex, browsers send user information in an encrypted form that still allows DSPs and advertisers to measure conversions, compute aggregate statistics such as histograms about users and their interests, and obliviously bid on auctions without learning for whom they are bidding. Our implementation of Ibex shows that creating histograms is 1.7–2.5× more expensive for browsers than disclosing user information, and Ibex’s oblivious bidding protocol can finish auctions within 550 ms. We think this makes Ibex capable of preserving a good experience while improving user privacy. 

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