Minimizing Power Consumption under SINR Constraints for Cell-Free Massive MIMO in O-RAN

Vaishnavi Kasuluru, Luis Blanco, Miguel Angel Vazquez, Cristian J. Vaca-Rubio, Engin Zeydan
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Abstract

This paper deals with the problem of energy consumption minimization in Open RAN cell-free (CF) massive Multiple-Input Multiple-Output (mMIMO) systems under minimum per-user signal-to-noise-plus-interference ratio (SINR) constraints. Considering that several access points (APs) are deployed with multiple antennas, and they jointly serve multiple users on the same time-frequency resources, we design the precoding vectors that minimize the system power consumption, while preserving a minimum SINR for each user. We use a simple, yet representative, power consumption model, which consists of a fixed term that models the power consumption due to activation of the AP and a variable one that depends on the transmitted power. The mentioned problem boils down to a binary-constrained quadratic optimization problem, which is strongly non-convex. In order to solve this problem, we resort to a novel approach, which is based on the penalized convex-concave procedure. The proposed approach can be implemented in an O-RAN cell-free mMIMO system as an xApp in the near-real time RIC (RAN intelligent Controller). Numerical results show the potential of this approach for dealing with joint precoding optimization and AP selection.
在 SINR 约束条件下最大限度降低 O-RAN 中无蜂窝大规模多输入多输出的功耗
考虑到多个接入点(AP)部署了多个天线,并在相同的时频资源上共同为多个用户提供服务,我们设计了最小化系统功耗的预编码向量,同时为每个用户保留了最小 SINR。我们使用了一个简单而又有代表性的功耗模型,它由一个固定项和一个可变项组成,固定项模拟 AP 激活时的功耗,可变项则取决于传输功率。上述问题可归结为二元受限二次优化问题,该问题具有强凸性。为了解决这个问题,我们采用了一种基于受惩罚凸凹过程的新方法。所提出的方法可以作为近实时 RIC(RAN 智能控制器)中的一个 xApp 在 O-RAN 无小区 mMIMO 系统中实现。数值结果表明了这种方法在处理联合预编码优化和接入点选择方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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