Load balancing and pricing for spectrum access control in cognitive radio networks

In dynamic spectrum access (DSA) control, the prevalent approach to provide economics incentives for operators is pricing, whereas load balancing gives congestion-avoidance incentives to secondary users (SUs). Despite complexities of i) the couplings between pricing, load balancing and SUs' spectrum access decision, and ii) the heterogeneity of primary users' traffic and SUs types, we propose to solve the joint load balancing and pricing problem to maximize operator' revenue in a monopoly market. In this market, we first show there exists a unique SUs' equilibrium arrival rate to the monopolist's channels, and then we show that the joint problem can be solved efficiently by exploiting its convex structure. We next propose a low-complexity algorithm that enable the operator to maximize its revenue.