Abstract Since Massive multiple-input and multiple-output (MIMO) and heterogeneous networks (HetNets) have significantly improvement in spectrum efficiency, Massive MIMO enabled HetNets have emerged as a promising technique for the fifth-generation cellular networks. Most previous studies focus on energy-efficient resource allocation of Massive MIMO HetNets by assuming perfect channel state information (CSI). In this paper, we investigate the α-fairness network utility optimization problem of joint user association and power allocation for a downlink Massive MIMO HetNet with imperfect CSI. By utilizing zero-forcing beamforming, we show a new closed-form lower bound expression on the ergodic achievable rate. Furthermore, we formulate the optimization problem as a mixed-integer nonlinear programming problem, which is non-convex and NP-hard, to achieve the maximization of α-fairness network utility. Consequently, a joint iterative algorithm with respect to user association and power allocation is developed by decomposing the original problem and relaxing the constraints. Simulation results show that our proposed algorithm can yield much better network utility performance than the other algorithms.

中文翻译：

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具有不完善 CSI 的大规模 MIMO HetNet 的联合用户关联和功率分配

摘要 由于大规模多输入多输出 (MIMO) 和异构网络 (HetNets) 显着提高了频谱效率，因此支持大规模 MIMO 的 HetNets 已成为第五代蜂窝网络的有前途的技术。以前的大多数研究都通过假设完美的信道状态信息 (CSI) 来关注大规模 MIMO HetNet 的节能资源分配。在本文中，我们研究了具有不完善 CSI 的下行链路 Massive MIMO HetNet 的联合用户关联和功率分配的 α 公平网络效用优化问题。通过利用迫零波束成形，我们展示了遍历可实现速率的新封闭形式下界表达式。此外，我们将优化问题表述为一个混合整数非线性规划问题，它是非凸和 NP 难的，以实现α-公平网络效用的最大化。因此，通过分解原始问题并放宽约束，开发了关于用户关联和功率分配的联合迭代算法。仿真结果表明，我们提出的算法可以产生比其他算法更好的网络效用性能。