With the rapid development of cloud computing, the user-centric networks with the baseband unit pool have attracted a great deal of attentions in academic and industrial fields. However, limited fronthaul capacity and computation resource have become the bottlenecks inevitably. Thus, this paper investigates the power-efficient transmission in user-centric networks by considering both fronthaul capacity and computation resource constraints, where multiple access points (APs) and user equipments (UEs) are distributed. Specifically, a joint optimization of the beamforming vectors, AP-UE association strategy and transmission time is proposed to minimize the total power consumption (TPC). The formulated mixed integer non-linear problem (MINLP) is NP-hard. To address this problem, the MINLP is first transformed into a convex one via the successive convex approximation and semidefinite relaxation methods. Then, an iterative but effective algorithm is designed by using the property of the solution and applying the Lagrangian dual method. Simulation results show that the proposed algorithm converges rapidly and outperforms benchmark algorithms in terms of TPC.

中文翻译：

---

前传容量和计算资源有限的以用户为中心的网络的节能传输


随着云计算的快速发展，以用户为中心的基带单元池网络引起了学术界和工业界的广泛关注。然而，有限的前传容量和计算资源不可避免地成为瓶颈。因此，本文通过考虑前传容量和计算资源限制，研究以用户为中心的网络中的节能传输，其中多个接入点（AP）和用户设备（UE）是分布式的。具体来说，提出了波束成形向量、AP-UE关联策略和传输时间的联合优化，以最小化总功耗（TPC）。公式化的混合整数非线性问题 (MINLP) 是 NP 难问题。为了解决这个问题，首先通过逐次凸逼近和半定松弛方法将 MINLP 转换为凸函数。然后，利用解的性质并应用拉格朗日对偶方法设计了一种迭代但有效的算法。仿真结果表明，该算法收敛速度快，并且在 TPC 方面优于基准算法。