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

TL;DR

This paper proposes an energy-efficient resource allocation method for multimedia H-CRANs, optimizing cooperative beamforming under fronthaul and interference constraints to balance energy efficiency and delay.

Contribution

It introduces a stochastic optimization framework using Lyapunov optimization for cooperative beamforming in multimedia H-CRANs with fronthaul and interference constraints.

Findings

Achieves a tradeoff between energy efficiency and queuing delay.

Fronthaul constraints significantly impact the EE-delay tradeoff.

Proposed method outperforms baseline schemes in simulations.

Abstract

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm which incorporates the cloud computing into heterogeneous networks (HetNets), thereby taking full advantage of cloud radio access networks (C-RANs) and HetNets. Characterizing the cooperative beamforming with fronthaul capacity and queue stability constraints is critical for multimedia applications to improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization objective function with individual fronthaul capacity and inter-tier interference constraints is presented in this paper for queue-aware multimedia H-CRANs. To solve this non-convex objective function, a stochastic optimization problem is reformulated by introducing the general Lyapunov optimization framework. Under the Lyapunov framework, this optimization problem is equivalent to an optimal network-wide cooperative beamformer design algorithm with instantaneous power, average power and inter-tier interference constraints, which can be regarded as the weighted sum EE maximization problem and solved by a generalized weighted minimum mean square 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.