Spectrum Sharing in MIMO Cognitive Radio Networks Based on Cooperative Game Theory

In a MIMO cognitive radio network, multiple secondary users sense the spatial channels and share the spectrum use with incumbent primary users. Each secondary transmitter competes with others to increase its own information rate while generating limited total interference to the primary receivers. In order to maximize the sum-rate of the cognitive radio network, the problem of secondary user transmission is modeled as a cooperative game. The strategy of each secondary user is the transmit covariance matrix, and the utility is an approximation of the information rate. The secondary users negotiate over the allocation of the interference budget and reach at a bargaining solution that maximizes the network utility. With well-designed individual utility and network utility functions, the bargaining solution is unique and Pareto optimal. An efficient distributed algorithm is developed that converges quickly to the optimal solution with moderate signaling within the network. Numerical results show the performance improvement in sum-rate of the MIMO cognitive radio network at the bargaining solution of the cooperative game compared with the Nash-equilibrium solution of the non-cooperative game.