Maximizing investment income of SSP for spectrum trading in cognitive radio networks
Lu Wang, Zhong Zhou, Wei Wu · 2014
More and more researches have demonstrated the benefits of cognitive radio technology in improving flexibility and efficiency of spectrum utilization. In order to encourage primary users (PUs) to share their idle spectrum resources with secondary users (SUs), spectrum trading frameworks are developed. In this paper, the investment problem of spectrum service provider (SSP) is considered which obtains spectrum from PUs and provides service to multiple SUs. The SUs' actions are estimated according to statistical data. A estimation method for channels number is proposed basing on maximizing the SSP's investment income. A Markov chain model is used to analyze the SSP's state transition and calculate the SU's waiting time and queuing size by queuing theory. The optimal number of channels is deduced with marginal analysis theory. In either spectrum purchase or auction, the SSP could adjust its investment strategy timely and flexibly according to these parameters.