Spectrum and Energy Cost Minimizing of Two Cooperating Cognitive Radio Network Base Stations

摘要

We consider a small TV White Space (TVWS)spectrum based Cognitive Radio Network (CRN), comprising of only two Base Stations (BSs), termed as TVWS-BSs. Each TVWS-BS is equipped with an energy harvesting source and, if required, it can also purchase energy from the grid. For data transmission on wireless channel, free TVWS spectrum is generally used. However, when free TVWS spectrum is unavailable, there is also an option of spectrum leasing to ensure Quality of Service (QoS) guarantees for some applications. To enable data and energy sharing, the two TVWS-BSs are also connected with each other on wired links. With varying availability of TVWS spectrum and harvested energy, varying spectrum leasing and energy purchase prices, and varying QoS requirements, our objective is to minimize the overall time average expected cost of spectrum and energy purchase. Using perturbed Lyapunov drift plus penalty function framework, we develop an online distributed algorithm called Lyapunov Data and Energy Transmission Algorithm (LDETA). This algorithm can be implemented by each TVWS-BS to make real-time decisions about spectrum leasing, energy purchase, data sharing, and energy sharing. The performance of the proposed algorithm is verified through simulations and shows significant gains compared to the cases with limited cooperation between the TVWS-BSs.