Dynamic resource optimization with congestion control in heterogeneous cloud radio access networks

The heterogeneous cloud radio access networks (H-CRANs) are presented in this paper as a promising new paradigm for future heterogeneous converged networks. To maintain low traffic queue congestion and make the sum utility of average throughput arbitrarily close to the optimum, the dynamic optimization problem of traffic admission control, heterogeneous processing node (HPN)/remote radio head (RRH) association, resource block (RB) and power allocation subject to the average power consumption constraints of RRHs is formulated using the general framework of Lyapunov optimization. The optimization problem can be decomposed into three subproblems. To solve the third mixed-integer subproblem, the continuity relaxation is utilized and the optimality can be still preserved. Finally, the simulation results validate the out-performances of the proposed solution with appropriate control parameter.