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首页> 外文期刊>IEEE transactions on multimedia >Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks
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Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks

机译：多媒体异构云无线接入网的节能资源分配优化

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摘要

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm that incorporates 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 critical for multimedia applications to improve the energy efficiency (EE) in H-CRANs. An energy-efficient optimization objective function with individual fronthaul capacity and intertier interference constraints is presented in this paper for queue-aware multimedia H-CRANs. To solve this nonconvex 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 intertier interference constraints, which can be regarded as a 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.
机译：异构云无线电接入网络（H-CRAN）是一种很有前途的范例，它将云计算整合到异构网络（HetNets）中，从而充分利用了云无线电接入网络（C-RAN）和HetNets。利用前传容量和队列稳定性约束来表征协作波束成形对于多媒体应用程序提高H-CRAN的能效（EE）至关重要。本文针对具有队列意识的多媒体H-CRAN，提出了具有单个前传容量和层间干扰约束的节能优化目标函数。为了解决这个非凸目标函数，通过引入一般的Lyapunov优化框架来重新构造一个随机优化问题。在Lyapunov框架下，此优化问题等效于具有瞬时功率，平均功率和层间干扰约束的最优全网协作波束成形器设计算法，该算法可以视为加权和EE最大化问题，并可以通过广义加权最小值来解决均方误差方法。数学分析和仿真结果表明，可以实现EE与排队延迟之间的折衷，并且这种折衷严格取决于前传约束。

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