PROJECT TITLE :

Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks

ABSTRACT:

The heterogeneous cloud radio access network (H-CRAN) may be a promising paradigm that includes Cloud Computing into heterogeneous networks (HetNets), thereby taking full advantage of cloud radio access networks (C-RANs) and HetNets. Characterizing cooperative beamforming with fronthaul capacity and queue stability constraints is vital for multimedia applications to enhance the energy efficiency (EE) in H-CRANs. An energy-efficient optimization objective function with individual fronthaul capability and intertier interference constraints is presented in this paper for queue-aware multimedia H-CRANs. To resolve this nonconvex objective perform, a stochastic optimization problem is reformulated by introducing the overall Lyapunov optimization framework. Under the Lyapunov framework, this optimization downside is adore an optimal network-wide cooperative beamformer style algorithm with instantaneous power, average power, and intertier interference constraints, that can be thought to be a weighted total EE maximization problem and solved by a generalized weighted minimum mean-sq. error approach. The mathematical analysis and simulation results demonstrate that a tradeoff between EE and queuing delay can be achieved, and this tradeoff strictly depends on the fronthaul constraint.