Ge Xiaohu, Sun Yang, Gharavi Hamid, Thompson John
School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.
National Institute of Standards and Technology (NIST), Gaithersburg, MD 20899-8920 USA.
IEEE Trans Wirel Commun. 2018;17. doi: 10.1109/TWC.2018.2819653.
With the growing interest in the deployment of massive multiple-input-multiple-output (MIMO) systems and millimeter wave technology for fifth generation (5G) wireless systems, the computation power to the total power consumption ratio is expected to increase rapidly due to high data traffic processing at the baseband unit. Therefore in this paper, a joint optimization problem of computation and communication power is formulated for multi-user massive MIMO systems with partially-connected structures of radio frequency (RF) transmission systems. When the computation power is considered for massiv MIMO systems, the results of this paper reveal that the energy efficiency of massive MIMO systems decreases with increasing the number of antennas and RF chains, which is contrary with the conventional energy efficiency analysis results of massive MIMO systems, i.e., only communication power is considered. To optimize the energy efficiency of multi-user massive MIMO systems, an upper bound on energy efficiency is derived. Considering the constraints on partially-connected structures, a suboptimal solution consisting of baseband and RF precoding matrices is proposed to approach the upper bound on energy efficiency of multi-user massive MIMO systems. Furthermore, an oPtimized Hybrid precOding with computation and commuNication powEr (PHONE) algorithm is developed to realize the joint optimization of computation and communication power. Simulation results indicate that the proposed algorithm improves energy and cost efficiencies and the maximum power saving is achieved by 76.59% for multi-user massive MIMO systems with partially-connected structures.
随着对将大规模多输入多输出（MIMO）系统和毫米波技术应用于第五代（5G）无线系统的兴趣日益浓厚，由于基带单元要处理大量数据流量，计算功率与总功耗之比预计将迅速增加。因此，本文针对具有部分连接结构的射频（RF）传输系统的多用户大规模MIMO系统，提出了计算和通信功率的联合优化问题。当考虑大规模MIMO系统的计算功率时，本文结果表明，大规模MIMO系统的能量效率会随着天线数量和射频链数量的增加而降低，这与传统的大规模MIMO系统能量效率分析结果相反，传统分析仅考虑通信功率。为了优化多用户大规模MIMO系统的能量效率，推导了能量效率的上限。考虑到部分连接结构的约束，提出了一种由基带和射频预编码矩阵组成的次优解决方案，以接近多用户大规模MIMO系统能量效率的上限。此外，还开发了一种具有计算和通信功率的优化混合预编码（PHONE）算法，以实现计算和通信功率的联合优化。仿真结果表明，所提算法提高了能量效率和成本效率，对于具有部分连接结构的多用户大规模MIMO系统，最大可节省功率达76.59%。
