Multi-Item Spectrum Auction for Recall-Based Cognitive Radio Networks With Multiple Heterogeneous Secondary Users

Abstract

In this paper, we consider a spectrum auction system among heterogeneous secondary users (SUs) with various quality-of-service (QoS) requirements and a recall-based primary base station (PBS) that could recall channels after auction to deal with a sudden increase in its own demand. Beginning with proposing a recall-based single-winner spectrum auction (RSSA) algorithm, we further extend our work to allow multiple winners in order to improve the spectrum utilization and propose a recall-based multiple-winner spectrum auction (RMSA) algorithm. A combinatorial auction model is then formulated, and Vickrey-Clarke-Groves (VCG) mechanism is applied in the payment function. Moreover, the proposed RMSA algorithm focuses on a fair spectrum allocation among heterogeneous SUs and the increase in the PBS's auction revenue. Both theoretical and simulation results show that the proposed spectrum auction algorithm can improve the spectrum utilization with guarantees on SUs' heterogeneous QoS requirements.