Resource Allocation of noncooperative multi-cell for cognitive radio networks
Résumé
Cognitive radio (CR) is proposed to improve frequency efficiency while avoiding interference with licensed users. In this paper, we adopt a resource allocation (RA) algorithm to perform uplink frequency allocation and power control between noncooperative multi-cell for CR network. The proposed RA algorithm is an extension of iterative water-filling algorithm (IWFA) applied to single-cell. The maximization of total information rates of multiple users in one cell is considered for Gaussian channel with pathloss, subject to power constraint on each user. By using multiple access channel (MAC) capacity region, the optimization problem is formulated as a decentralized game, in which each base station, trying to maximize the sum-rate of its own users, is a player, and Nash equilibrium (NE) can be achieved to guarantee global convergence. Our algorithm shows higher sum-rate than the traditional FDMA by sharing one and more subcarriers for different users. Final simulation results show that our algorithm can achieve more information rate than fixed channel allocation algorithm.