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Optimal ADMM-Based Spectrum and Power Allocation for Heterogeneous Small-Cell Networks with Hybrid Energy Supplies

机译:具有混合能源供应的非均质小型电池网络的基于最佳ADMM的频谱和功率分配

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Powering cellular networks with hybrid energy supplies is not only environment-friendly but can also reduce the on-grid energy consumption, thus being emerging as a promising solution for green networking. Intelligent management of spectrum and power can increase the network utility in cellular networks with hybrid energy supplies, usually at the cost of higher energy consumption. Unlike prior studies on either the network utility maximization or on-grid energy cost minimization, this paper studies the joint spectrum and power allocation problem that maximizes the system revenue in a heterogeneous small-cell network with hybrid energy supplies. Specifically, the system revenue is considered as the difference between the network utility and on-grid energy cost. By developing the convexity of the optimization problem through transformation and reparameterization, we propose a joint spectrum and power allocation algorithm based on the primal-dual arguments to obtain the optimal solution by iteratively solving the primal and dual sub-problems of the convex optimization problem. To solve the primal sub-problem, we further propose the Lagrangian maximization based on the alternating direction method of multipliers (ADMM), and derive the optimal solution in the closed-form expression at each iteration. It is shown that the proposed joint spectrum and power allocation algorithm approaches the global optimality at the rate of 1 with n being the number of iterations. Also, the proposed ADMM-based Lagrangian maximization algorithm approaches the primal optimal solution with the time complexity of O(1/(r)) iterations with is an element of(r) being the termination parameter. Simulation results show that in comparison with the power control with equal frequency allocation algorithm and frequency allocation with equal power allocation algorithms the proposed algorithm increases the systemrevenue by over 20 and 60 percent without consuming more on-grid energy when the proportional fairness utility and the weighted sum rate utility are considered with the approximate system parameter settings, respectively. Meanwhile, in comparison with the full frequency reuse case, the proposed algorithm increases the systemrevenue by 20 percent at least in terms of the weighted sum rate utility, although it achieves the similar systemrevenue when considering the proportional fairness utility. Simulation results also show that our proposed algorithmcan performwell under the realistic fast fading channel conditions.
机译:用混合能源供应供电的蜂窝网络不仅是环保的,而且还可以降低网格能源消耗,从而成为绿色网络的有希望的解决方案。频谱和功率的智能管理可以增加具有混合能源供应的蜂窝网络中的网络实用性,通常以更高的能耗成本。与对网络实用性最大化或盖子能源成本最小化的先前研究不同,本文研究了具有混合能源供应的异构小型电池网络中的系统收入的联合频谱和功率分配问题。具体而言,系统收入被认为是网络实用程序与网格能源成本之间的差异。通过转换和重新支柱化开发优化问题的凸性,我们提出了一种基于原始参数的联合频谱和功率分配算法,以通过迭代解决凸优化问题的原始和双子问题来获得最佳解决方案。为了解决原始子问题,我们进一步提出了基于乘法器(ADMM)的交替方向方法的拉格朗日最大化,并在每次迭代中导出闭合形式表达中的最佳解决方案。结果表明,所提出的联合频谱和功率分配算法以1 / n的速率接近全局最优,是n的迭代次数。此外,所提出的基于ADMM的拉格朗日最大化算法与O(1 /(r))迭代的时间复杂度接近原始最佳解决方案是(R)是终端参数的元素。仿真结果表明,与等电功率分配算法的电力控制和具有相等功率分配算法的频率分配相比,所提出的算法在比例公平效用和加权时,在不产生更多的网格能量的情况下将Systemrevene增加到20%和60%。分别使用近似系统参数设置考虑总和率实用程序。同时,与全频重用案例相比,所提出的算法至少在加权总和率效用方面将Systemrevene增加了20%,尽管在考虑比例公​​平实用程序时实现了类似的Systemrevenue。仿真结果还表明,我们所提出的算法在现实的快速衰落信道条件下执行良好。

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