Power Optimization for Massive MIMO Systems With Hybrid Energy Harvesting Transmitter
Power Optimization for Massive MIMO Systems With Hybrid Energy Harvesting Transmitter
复制标题
使用混合能量收集发射器的大规模 MIMO 系统的功率优化
DOI：
10.1109/tvt.2018.2854719
复制
发表时间：
2018
影响因子：
6.8
通讯作者：
ong
中科院分区：
文献类型：
--
作者：
Zhang Yang;Zhang Dan;Pang Lihua;Chi Mingjie;Li Yi;Ren Guangliang;Li Ji;ong
本文研究了在具有混合能量收集发射机的大规模多输入多输出（MIMO）下行链路网络中，以吞吐量最大化为目标的功率优化问题。特别地，在基站处结合固定电网采用有限容量的能量采集器以用于系统能量供应。随着信道状态信息（CSI）和能量收集过程的非因果知识的可用性，吞吐量最大化首先制定为一个典型的凸优化问题，受一组电池存储和功率约束。特别是，这种优化的特点还考虑到电路的能量消耗，不能忽视的大规模MIMO系统与大质量的射频链。在数学上，可以使用拉格朗日对偶分解技术来导出最优功率变量。然而，由于其离线计算的特点，所提出的方法是难以实现的，在实践中，只能作为一个性能上界。为了方便真实的世界的应用，我们然后，简要地提出了一个在线计划，仅仅利用因果信息的CSI和统计的能量收集过程中，没有显着降低性能。最后通过仿真验证了算法的有效性。
We investigate power optimization for throughput maximization in massive multiple-input multiple-output (MIMO) downlink networks with hybrid energy harvesting transmitter. In particular, a finite-capacity energy harvester is employed at the base station in conjunction with the fixed power grid for system energy supply. With availability of the noncausal knowledge about the channel state information (CSI) and the energy harvesting process, the throughput maximization is first formulated as a typical convex optimization problem, subject to a set of battery storage and power constraints. Especifically, this optimization is also featured by taking into account the circuit energy consumption that can not be neglected in massive MIMO systems with a large quality of radio frequency chains. Mathematically, Lagrange dual decomposition technique can be used to derive the optimal power variables. However, due to its offline calculation characteristics, the proposed approach is hard to implement in practice and can only serve as a performance upper bound. To facilitate real world application, we then heuristically present an online scheme that merely utilizes the causal information of the CSI and the statistics of the energy harvesting process, without significantly degrading the performance. Finally, simulation results are shown to verify the effectiveness of the proposed algorithms.