Smart spectrum access algorithms in mobile TV white space networks for utility maximization

We study a utility maximization framework for spectrum sharing among unlicensed secondary users and licensed primary users in mobile TV white space networks. All the users maximize the network utility by adapting their signal-to-interference-plus-noise ratio (SINR) assignment and transmit power subject to power budget constraints and additional interference temperature constraints for the secondary users. By exploiting the nonnegative matrix theory, we first reformulate the utility maximization problem as an equivalent optimization problem involving spectral radius constraints and with SINR as its only variable. To proceed further, we studied a special case that maximizes the egalitarian fairness of all the SINRs as the utility (also known as the max-min weighted SINR). Then, we solve the general utility maximization by developing a novel cognitive radio network duality to decouple the SINR assignment, the transmit power and the interference temperature allocation. A projected subgadient method is proposed to joinly optimize the power and the interference temperature. This algorithm has the advantage that it can be distributively implemented, and the method converges relatively fast.