Beam management in 5G NR involves the transmission and reception of control signals such as Synchronization Signal Blocks (SSBs), crucial for tasks like initial access and/or channel estimation. However, this procedure consumes energy, which is particularly challenging to handle for battery-constrained nodes such as RedCap devices. Specifically, in this work we study a mid-market Internet of Things (IoT) Smart Agriculture (SmA) deployment where an Unmanned Autonomous Vehicle (UAV) acts as a base station "from the sky" (UAV-gNB) to monitor and control ground User Equipments (UEs) in the field. Then, we formalize a multi-variate optimization problem to determine the optimal beam management design for RedCap SmA devices in order to reduce the energy consumption at the UAV-gNB. Specifically, we jointly optimize the transmission power and the beamwidth at the UAV-gNB. Based on the analysis, we derive the so-called "regions of feasibility," i.e., the upper limit(s) of the beam management parameters for which RedCap Quality of Service (QoS) and energy constraints are met. We study the impact of factors like the total transmission power at the gNB, the Signal-to-Noise Ratio (SNR) threshold for successful packet decoding, the number of UEs in the region, and the misdetection probability. Simulation results demonstrate that there exists an optimal configuration for beam management to promote energy efficiency, which depends on the speed of the UEs, the beamwidth, and other network parameters.

翻译：5G NR中的波束管理涉及同步信号块（SSBs）等控制信号的发送与接收，这对初始接入和/或信道估计等任务至关重要。然而，该过程会产生能耗，对于RedCap设备等电池受限节点而言尤为棘手。本研究聚焦于一种中端物联网（IoT）智能农业（SmA）部署场景：其中无人自主飞行器（UAV）充当“空中基站”（UAV-gNB），对地面用户设备（UEs）进行监测与控制。我们构建了一个多变量优化问题，以确定RedCap SmA设备的最优波束管理设计方案，从而降低UAV-gNB的能耗。具体而言，我们联合优化了UAV-gNB的发射功率和波束宽度。基于分析，推导出所谓的“可行性区域”，即满足RedCap服务质量（QoS）与能量约束的波束管理参数上限。我们进一步研究了gNB总发射功率、成功数据包解码的信噪比（SNR）阈值、区域内UE数量以及漏检概率等因素的影响。仿真结果表明，存在一种促进能效的波束管理最优配置，该配置取决于用户设备速度、波束宽度及其他网络参数。