In this study, 5G- NB-IoT, enabled smart urban farming framework is presented. In order to maximize the Energy-Efficiency (EE) of NB-IoT enabled sensor network's downlink performance (deployed in urban structure), 5 G promising technology device to device (D2D) communication along with power-domain Non-Orthogonal-Multiple-Access (NOMA) principle were used and studied at two levels, i.e. NOMA-at- Base Station (BS) and NOMA-at-Edge. In the case of NOMA-at-BS, the BS transmits the superimposed signals to the NB-IoT-enabled sensor D2D pairs (termed as NOMA-D2D approach). Whereas in the case of NOMA at the Edge, in the group of NB-IoT enabled sensor nodes, the group head will transmit the superimposed signals to other group receiver sensor nodes (termed as Group-NOMA-D2D approach). These suggested solutions, ensure interference-free communication among deployed NB-IoT enabled sensor networks. The proposed approaches were implemented on the NB-IoT sensor network (deployed in balconies of two multistory building structures) and their results were evaluated through simulation. The promising enhancement in terms of sum-rate (32% to 35 %), total-energy efficiency, and fairness factor (1- 0.98) has been achieved using the Group NOMA-D2D approach in comparison to NOMA-D2D and conventional D2D approach. In addition to this, a fuzzy logic-aided solution has also been proposed for NB-IoT enabled sensor network, uplink resource grant, and post allocation resource re-utilization, this, in turn, improved the Quality of Experience (QoE) by 2–14%.

在这项研究中，5G-NB-IoT 启用了智能城市农业框架。为了最大限度地提高支持 NB-IoT 的传感器网络的下行链路性能（部署在城市结构中）的能源效率 (EE)，5G 有前途的技术设备到设备 (D2D) 通信以及功率域非正交多址(NOMA) 原理在两个层面上被使用和研究，即NOMA-at-Base Station (BS)和NOMA-at-Edge。在NOMA-at-BS的情况下，BS 将叠加信号传输到支持 NB-IoT 的传感器 D2D 对（称为 NOMA-D2D 方法）。而在边缘的NOMA的情况下, 在启用 NB-IoT 的传感器节点组中，组长将叠加信号传输到其他组接收器传感器节点（称为 Group-NOMA-D2D 方法）。这些建议的解决方案可确保已部署的支持 NB-IoT 的传感器网络之间的无干扰通信。所提出的方法在 NB-IoT 传感器网络（部署在两个多层建筑结构的阳台上）上实施，并通过模拟评估了它们的结果。与 NOMA-D2D 和传统 D2D 方法相比，使用 Group NOMA-D2D 方法在总和率（32% 至 35%）、总能源效率和公平系数（1-0.98）方面实现了有希望的增强. 除此之外，还针对支持 NB-IoT 的传感器网络、上行链路资源授予和后分配资源再利用提出了模糊逻辑辅助解决方案，这反过来又将体验质量 (QoE) 提高了 2 –14%。