Privacy-Preserving Spectrum Allocation in Cognitive Radio Networks Based on Truthful Online Double Auction Mechanism

Abstract

Cognitive radio can improve spectrum utilization through spectrum sharing between primary and secondary users, thereby alleviating spectrum scarcity. Spectrum auction is one of the effective methods that can be utilized to achieve spectrum sharing. However, traditional spectrum auction is unable to guarantee the truth of the price given by bidders comprehensively, while neglecting the online characteristics of the buyers request arrival. Existing truthful online auction mechanisms do not consider the privacy leakage problem and fail to provide adequate privacy protection for bidders. In this paper, we propose a privacy-preserving spectrum allocation strategy based on a double online truthful auction mechanism. Specifically, we first propose a critical bid determination algorithm to guarantee the truth of the auction. Then, the channel allocation is modeled as a social welfare maximization optimization problem. Since the problem is NP-hard and it is difficult to solve in polynomial time. We propose a greedy algorithm that can effectively obtain a feasible solution to the problem. An online dynamic accessing mechanism is further designed by considering the arrival of requests of secondary users. Finally, differential privacy is introduced to encrypt sensitive information such as buyers location privacy and time dynamic. Experimental results validate our auction mechanism achieving higher social welfare and spectrum utilization.