Matching Theory based Privacy Preserving Dynamic Spectrum Sharing for Next Generation Wireless Networks

Communication spectrum is becoming a scarce asset in recent years. Spectrum efficiency has become crucial as the demand for wireless networks is growing very fast. Dynamic spectrum sharing is the most efficient way to maximize the use of spectrum resources among Secondary Users (SUs) and Primary Users (PUs) through sharing to meet the growing spectrum demands. While spectrum trading or sharing is the key to solving spectrum scarcity and utilization, it is subject to SUs’ bid privacy preservation issues, and PUs’ revenue maximization goals. In this paper, we propose a scheme that ensures both SUs’ bid privacy and enhances PUs’ revenue maximization. We propose a spectrum sharing framework that explores Paillier Cryptosystem for privacy preservation, Conflict Graphs for spectrum reuse, and Matching Theory based distributed architecture for maximizing PUs’ revenue. This work addresses many limitations that are observed when transitioning theoretical privacy methods into practice.