Ultra-dense HetNets (UDN)-based Millimeter-Wave (mmWave) massive MIMO is considered a promising technology for 5th generation (5G) wireless communications systems since it can offer massively available bandwidth and improve energy efficiency (EE) substantially. However, in UDN, the power consumption of the system increases sharply with the increase of network density. In this paper, we investigate the optimization of the EE in the mmWave massive MIMO systems with UDN. To develop the functions of massive MIMO, we first propose a system model where the massive MIMO harvests electromagnetic energy from the environment employing simultaneous wireless information and power transfer (SWIPT) technology, implemented at the base station (BS). Then, the EE optimization problem is formulated for 5G mmWave massive MIMO systems within the UDN. Considering the nonconcave feature of the objective function, an iterative EE algorithm is developed, based on Dinkelbach method. To utilize the role of coordinated multi-point transmission and reception (CoMP) for improving the EE, a coordinated user(UE)-BS association algorithm-based CoMP with maximum energy efficiency (MaxEE) is proposed. The simulation results demonstrate that the proposed algorithm has a substantially faster convergence rate and is very effective, compared with existing methods.

中文翻译：

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通过 SWIPT 和 CoMP 在超密集 HetNet 中使用毫米波大规模 MIMO 进行节能资源分配

基于超密集 HetNets (UDN) 的毫米波 (mmWave) 大规模 MIMO 被认为是第五代 (5G) 无线通信系统的一项有前途的技术，因为它可以提供大量可用带宽并显着提高能源效率 (EE)。但是，在UDN中，系统的功耗随着网络密度的增加而急剧增加。在本文中，我们研究了使用 UDN 的毫米波大规模 MIMO 系统中的 EE 优化。为了开发大规模 MIMO 的功能，我们首先提出了一个系统模型，其中大规模 MIMO 使用同步无线信息和功率传输 (SWIPT) 技术从环境中收集电磁能量，并在基站 (BS) 上实施。然后，针对 UDN 内的 5G 毫米波大规模 MIMO 系统制定了 EE 优化问题。考虑到目标函数的非凹特征，基于Dinkelbach方法开发了一种迭代EE算法。为了利用协作多点发送和接收(CoMP)的作用来提高EE，提出了一种基于协作用户(UE)-BS关联算法的最大能效CoMP(MaxEE)。仿真结果表明，与现有方法相比，所提出的算法具有明显更快的收敛速度并且非常有效。