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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Differentially-Private Incentive Mechanism for Crowdsourced Radio Environment Map Construction
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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- Award ID(s):
- 1651954
- NSF-PAR ID:
- 10094441
- Date Published:
- Journal Name:
- IEEE International Conference on Computer Communications
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Database-driven Dynamic Spectrum Sharing (DSS) is the de-facto technical paradigm adopted by Federal Communications Commission for increasing spectrum efficiency, which allows licensed spectrum to be opportunistically used by secondary users. In database-driven DSS, a geo-location database administrator (DBA) maintains spectrum availability information over its service region in the form of a Radio Environment Map (REM), where the received signal strength from the primary user at every location is either directly measured via spectrum sensing or estimated via statistical spatial interpolation. Crowdsourcing-based spectrum sensing is a promising approach for periodically collecting spectrum measurements over a large geographic area but is unfortunately vulnerable to false spectrum measurements. Despite a large body of prior work on secure cooperative spectrum sensing, how to construct an accurate REM in the presence of false measurements remains an open challenge. In this paper, we introduce ST-REM, a novel spatiotemporal approach for securely constructing an REM in the presence of false spectrum measurements. Inspired by the self-label techniques developed for semi-supervised learning, ST-REM iteratively constructs an REM from a small number of spectrum measurements from trusted anchor sensors and many more measurements from mobile users. During each iteration, the DBA evaluates the trustworthiness of each measurement by jointly considering its spatial fitness with other trusted measurements and the mobile user's long-term behavior. By gradually incorporating the most trustworthy spectrum measurements, the DBA is able to construct a REM with high accuracy. Extensive simulation studies using a real spectrum measurement dataset confirm the efficacy and efficiency of ST-REM.more » « less
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Database-driven Dynamic Spectrum Sharing (DSS) is the de-facto technical paradigm adopted by Federal Communications Commission (FCC) for increasing spectrum efficiency. In such a system, a geo-location database administrator (DBA) maintains spectrum availability information over its service region whereby to determines whether a secondary user can access a licensed spectrum band at his desired location and time. To maintain spectrum availability in its service region, it is desirable for the DBA to periodically collect spectrum measurements whereby to construct and maintain a Radio Environment Map (REM), where the received signal strength at every location of interest is either directly measured or estimated via proper statistical spatial interpolation techniques. Crowdsourcing-based spectrum sensing is a promising approach for periodically collecting spectrum measurements over a large geographic area, which is, unfortunately, vulnerable to false spectrum measurements. How to construct an accurate REM in the presence of false measurements remains an open challenge. This paper introduces SecREM, a novel scheme for securely constructing a REM in the presence of false spectrum measurements. SecREM relies on a small number of trusted spectrum measurements whereby to evaluate the trustworthiness of the measurements from mobile users and gradually incorporate the most trustworthy ones to construct an accurate REM. Extensive simulation studies based on a real spectrum measurement dataset confirm the efficacy and efficiency of SecREM.more » « less
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Accepted Manuscript1.0
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