As a promising technology with disruptive innovation, user-centric network can meet the data traffic demand and user service demand in the future mobile networks. It completely transforms the traditional cell-centric paradigm into user-centric paradigm, requiring the deployment of a large number of access points (APs). However, the massive deployment of APs leads to issues such as high hardware cost, huge power consumption and complex interference management. Reconfigurable intelligent surfaces (RIS), as another promising technology, can expand signal coverage, suppress interference, reduce hardware cost and power consumption. Inspired by this, we propose a novel RIS assisted user-centric network that uses RIS to replace some low utilization APs to reduce cost as well as power consumption, and deploy more RIS to achieve energy-efficient user-centric communication. In order to take full advantages of RIS, we jointly optimize passive beamforming at RIS and power control at AP to maximize the energy efficiency of the network. Since this problem is intractable and non-convex, an effectively alternating optimization algorithm, capitalizing on fractional programming and successive lower-bound maximization is proposed. The simulation results verify that the proposed algorithm outperforms reference algorithms in terms of energy efficiency and sum rate.

中文翻译：

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可重构智能表面辅助用户中心网络中的联合功率控制和无源波束成形

以用户为中心的网络作为一项具有颠覆性创新前景的技术，可以满足未来移动网络的数据流量需求和用户服务需求。它将传统的以小区为中心的范式彻底转变为以用户为中心的范式，需要部署大量的接入点（AP）。然而，AP的大规模部署带来了硬件成本高、功耗大、干扰管理复杂等问题。可重构智能表面（RIS）作为另一种很有前途的技术，可以扩大信号覆盖范围、抑制干扰、降低硬件成本和功耗。受此启发，我们提出了一种新颖的 RIS 辅助以用户为中心的网络，该网络使用 RIS 替换一些低利用率的 AP 以降低成本和功耗，并部署更多的RIS，以实现以用户为中心的节能通信。为了充分发挥 RIS 的优势，我们联合优化了 RIS 的被动波束形成和 AP 的功率控制，以最大限度地提高网络的能源效率。由于这个问题是棘手的和非凸的，因此提出了一种有效的交替优化算法，利用分数规划和连续下界最大化。仿真结果验证了所提出的算法在能效和总和率方面优于参考算法。提出了利用分数规划和连续下限最大化。仿真结果验证了所提出的算法在能效和总和率方面优于参考算法。提出了利用分数规划和连续下限最大化。仿真结果验证了所提出的算法在能效和总和率方面优于参考算法。