Energy Efficiency Maximization Framework in Cognitive Downlink Two-Tier Networks
Energy Efficiency Maximization Framework in Cognitive Downlink Two-Tier Networks
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DOI：
10.1109/twc.2014.2367032
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发表时间：
2015-03
影响因子：
10.4
通讯作者：
Rindranirina Ramamonjison;V. Bhargava
中科院分区：
文献类型：
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作者：
Rindranirina Ramamonjison;V. Bhargava
为了支持无线数据流量的激增，蜂窝网络的频谱和能量效率应该大大提高。异构的两层体系结构已被确定为一个关键的解决方案。然而，小小区部署提出了关于由此产生的能量效率和干扰缓解的问题。因此，我们提出了一种能量有效的和认知的频谱共享方案之间的主宏小区和辅助小小区。具体地，小小区分配它们的传输功率以最大化它们的总能量效率，同时尊重由宏小区用户施加的一些干扰约束。我们分两步解决这个集中式优化。首先，假设小小区传输是无干扰的，使用凸参数方法来表征该非凸优化的解。利用这一特征，我们得到了一个基于牛顿法的算法，该算法收敛于全局最优解。其次，当小小区传输不一定是正交的，我们推导出一个算法，它至少收敛到一个局部最优，使用最小化最大化原则和牛顿法。通过仿真，我们验证了这些算法的收敛性，并比较其性能与现有的计划。我们还分析了干扰和用户数量对能量效率的影响。
To support the surge in wireless data traffic, the spectrum and energy efficiencies of cellular networks should be largely increased. Heterogeneous two-tier architecture has been identified as one key solution. However, small-cell deployment raises questions about the resulting energy efficiency and interference mitigation. Therefore, we propose an energy-efficient and cognitive spectrum sharing scheme between primary macrocell and secondary small cells. Specifically, the small cells allocate their transmission power to maximize their total energy efficiency while respecting some interference constraints imposed by macrocell users. We solve this centralized optimization in two steps. First, assuming that the small-cell transmissions are noninterfering, the solution of this nonconvex optimization is characterized using a convex parametric approach. Using this characterization, we derive an algorithm based on Newton method, which converges to a global optimal solution. Second, when the small-cell transmissions are not necessarily orthogonal, we derive an algorithm, which converges at least to a local optimum, using the minorization-maximization principle and Newton method. Through simulations, we validate the convergence of these algorithms and compare their performance with existing schemes. We also analyze the effects of the interference and of the number of users on the energy efficiency.