Network utility maximization of MIMO cognitive radio network with total interference-power constraints

In a MIMO cognitive radio network, multiple secondary users sense the spatial channels and share the spectrum with incumbent primary users. Each secondary transmitter competes with others to increase its own information rate while limiting interference to the primary receivers. In this paper, we consider the interference constraint as the total interference power at the primary receiver caused by all the secondary transmissions. The problem of optimal secondary transmissions is modeled as a network utility maximization problem. The network utility function takes the weighted sum or the product of the maximum information rates achievable by the secondary users. With approximation that decouples the individual utilities of different secondary users, the network utility maximization problem becomes convex and has a unique solution. Cooperative game is adopted for the secondary transmissions in order to reach a Pareto-efficient equilibrium. A distributed algorithm is further developed that converges quickly to the Nash bargaining solution with moderate signaling within the secondary user network.