Mode Selection and Power Optimization for Energy Efficiency in Uplink Virtual MIMO Systems
Mode Selection and Power Optimization for Energy Efficiency in Uplink Virtual MIMO Systems
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DOI：
10.1109/jsac.2013.130511
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发表时间：
2013-04
影响因子：
16.4
通讯作者：
Yun Rui;Keith Q. T. Zhang;Lei Deng;Peng Cheng;Mingqi Li
中科院分区：
文献类型：
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作者：
Yun Rui;Keith Q. T. Zhang;Lei Deng;Peng Cheng;Mingqi Li
在绿色通信的推动下，节能传输正成为无线系统设计的重要标准，旨在延长移动设备中电池的生命周期。本文主要研究上行虚拟多输入多输出（MIMO）系统的能量效率问题，该问题需要优化虚拟多输入多输出（MIMO）系统中两个相互交织的参数：虚拟MIMO中的移动用户数量及其相应的功率分配。前一个参数是定义虚拟MIMO（通常称为传输模式）大小的结构参数，其优化依赖于枚举方法。即使对于给定的传输模式，EE也是功率的非凸函数，这一事实进一步加剧了困难。通过利用增加活跃用户数量一方面可以增加总EE的贡献者数量，另一方面可以降低单个用户的多样性顺序，我们可以证明存在最优传播模式，并找到一种简单的搜索方式。通过深入分析，我们证明了在无功率约束的情况下，在零强迫接收机的假设下，存在唯一的全局最优功率分配，并进一步揭示了功率约束对功率分配的影响，与之相比，旨在为功率约束下的EE优化提供有力的手段。最后，我们为等距网络建立了理论，以缩小可能传输模式的搜索范围，从而大大降低了优化的计算复杂度。仿真结果证实了所提出的方案和相应的理论。
Driven by green communications, energy-efficient transmission is becoming an important design criterion for wireless systems, aiming to extend the life cycle of batteries in mobile devices. In this paper, we tackle the energy efficiency (EE) issue in uplink virtual multiple-input multiple-output (MIMO) systems, which requires the optimization of two interlaced parameters: the number of constituent mobile users in the virtual MIMO and their corresponding power allocation. The former parameter is a structural parameter defining the size of the virtual MIMO (usually known as the transmission mode) and its optimization relies on the method of enumeration. The difficulty is further aggravated by the fact that the EE is a non-convex function of power, even for a given transmission mode. By exploiting the fact that increasing the number of active users can increase the number of contributors to the total EE on one hand but reducing the diversity order for each single user on the other, we can show the existence of an optimal transmission mode and find a simple way for its search. Through in-depth analysis, we show the existence of a unique globally optimal power allocator for the case without power constraints under the assumption of zero-forcing receivers, and further reveal the impact of power constraints upon power allocation, as compared to its global counterpart, aiming to provide a powerful means for power-constrained EE optimization. Finally, we establish theories, for isometric networks, to narrow down the search range for possible transmission modes, leading to a significant reduction of computational complexity in optimization. Simulation results are presented to substantiate the proposed schemes and the corresponding theories.