A spectrum auction algorithm for cognitive distributed antenna systems

Distribute antenna system (DAS) can provide high date rate transmission to satisfy the service requirements for the rapid growing wireless applications. Besides, the increasing deployment of wireless applications make the demand for spectrum resource grow rapidly, thus cognitive radio (CR) has emerged as a promising technology to improve spectrum utilization, and spectrum auction is a promising approach to allocate spectrum bands in CR. A few existing works considered the combination of DAS and CR to get better system performance, but they have never studied the spectrum auction in these systems. In this paper, we will study the spectrum auction problem for cognitive DAS to improve spectrum utilization. Cognitive DAS with antennas deployed in a distributed manner in the secondary system can achieve higher spectrum utilization and reduce interference between primary users (PUs) and secondary users (SUs), and thus we can get a better system performance. According to the performance of SUs that can be obtained in cognitive DAS, the SUs compete for PU's licensed spectrum bands through auction. The objective of the spectrum auction is to maximize social welfare, which is formulated as an integer programming problem to allocate spectrum bands to SUs who value them best. A Lagrangian relaxation algorithm is developed to obtain the optimal allocation. Finally, we demonstrate the performance of the cognitive DAS and the auction mechanism through simulations.