...
首页> 外文期刊>IEEE Transactions on Communications >Energy-Efficient Resource Allocation for OFDMA Heterogeneous Networks
【24h】

Energy-Efficient Resource Allocation for OFDMA Heterogeneous Networks

机译:OFDMA异构网络的节能资源分配

获取原文
获取原文并翻译 | 示例

摘要

We proposed several energy-efficient resource allocation algorithms for the downlink of an orthogonal frequency-division-multiple-access (OFDMA) based femtocell heterogeneous networks (HetNets). Heterogeneous QoS and fairness in rate are investigated in the proposed resource allocation problem. A dense deployment of femtocells in the coverage area of a central macrocell is considered and energy usage of both femtocell and macrocell users are optimized simultaneously. We aim to maximize the weighted sum of the individual energy efficiencies (WSEEMax) and the network energy efficiency (NEEMax) while satisfying the following: (1) minimum throughput for delay-sensitive (DS) users, (2) fairness constraint for delay-tolerant (DT) users, (3) required constraints of OFDMA systems. The problem is formulated in three different forms: mixed 0-1 integer programming formulation, time-sharing formulation and sparsity-inducing formulation. The proposed resource block (RB) and power optimization problems are combinatorial and highly non-convex due to the fractional form of the objective function, the integer constraint of OFDMA RBs and non-affine fairness. We adopt the successive convex approximation (SCA) approach and transform the problems into a sequence of convex subproblems. With the proposed algorithms, we show that the overall joint RB and power allocation schemes converge to suboptimal solutions. Numerical examples confirm the merits of the proposed algorithms.
机译:针对基于正交频分多址(OFDMA)的毫微微小区异构网络(HetNets)的下行链路,我们提出了几种节能的资源分配算法。在提出的资源分配问题中研究了异构QoS和速率公平性。考虑到在中央宏小区的覆盖区域中密集部署毫微微小区,并且同时优化了毫微微小区和宏小区用户的能源使用。我们的目标是在满足以下条件的同时,最大化各个能源效率(WSEEMax)和网络能源效率(NEEMax)的加权总和:(1)延迟敏感(DS)用户的最小吞吐量,(2)延迟-容忍(DT)用户,(3)OFDMA系统的要求约束。该问题以三种不同形式表示:混合的0-1整数编程形式,分时形式和稀疏性引起形式。由于目标函数的分数形式,OFDMA RB的整数约束和非仿射公平性,所提出的资源块(RB)和功率优化问题是组合的且高度不凸。我们采用逐次凸逼近法(SCA),并将问题转化为一系列凸子问题。使用所提出的算法,我们表明整体联合RB和功率分配方案收敛于次优解决方案。数值例子证实了所提出算法的优点。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号