Truthful multi-attribute auction with discriminatory pricing in cognitive radio networks

Abstract

In this paper, we design a market-based channel allocation scheme for cognitive radio networks by exploiting multi-attribute channel-aware auctions to consider channel diversity in frequency, time, and space domains. Different from existing research, our objective is to maximize the winning SUs' service satisfaction degree while enhancing the utilities of winning PUs and SUs, which can effectively encourage them to join the auction and improve the sustainability of the spectrum market. Based on an elaborately devised preference function, we allocate channels to SUs satisfying their demands while considering spatial and temporal channel reuse to enhance channel utilization. Moreover, we propose a discriminatory pricing method to enhance the utilities of winning PUs and SUs. A comprehensive analysis indicates that our multi-attribute auction is individually-rational, ex-post budget balanced, value-truthful, and attribute-truthful. Our simulation results indicate that the proposed multi-attribute auction can significantly increase the winners' utilities and ensure SUs' service satisfaction.