Bid Privacy Preservation in Matching-Based Multiradio Multichannel Spectrum Trading

Abstract

Spectrum trading with secondary users (SUs) for monetary gains improves the inefficient spectrum utilization of primary users (PUs) in the cognitive radio networks (CRNs). It is an efficient way of dynamic spectrum sharing that enhances accessing opportunities of SUs and escalates revenue of PUs. In the spectrum trading market, bidding privacy is a serious concern for SUs, since untrustworthy PUs or spectrum traders may leverage bidding information to manipulate the trading or leak SU's bids to other SU competitors for illegal gains. Current centralized privacy preserving spectrum trading designs may incur extra infrastructure deployment, miss many instantaneous spectrum accessing opportunities, and have scalability issues. In this paper, we propose a privacy-preserving semidistributed spectrum trading scheme for multiradio multichannel CRNs, which has joint consideration of spectrum reuse, SUs’ bidding privacy preservation, and PUs’ revenue maximization. We use the conflict graph to characterize SUs’ interference relationships, and jointly employ the Paillier Cryptosystem and dynamic matching to conduct the spectrum trading in a semidistributed manner. Through security, complexity and performance analysis, we show that the proposed scheme 1) effectively preserves the privacy of SUs’ bidding values, and 2) notably increases the PUs’ revenue and improves spectrum utilization with limited overhead.