# Spectral and Energy Efficiency Trade-Off in UAV-Based Olive Irrigation Systems
###### Abstract  
Precision agriculture, also referred to as smart farming, is one of the main pillars of modern society to achieve the Sustainable Development Goals (SDGs). Precision agriculture aims to improve the quality and quantity of production while conserving scarce natural resources. Smart farming has grown in recent years thanks to the adoption of modern technologies, including artificial intelligence (AI) and the Internet of Things (IoT). In this work, we consider an irrigation system for olive orchards based on unmanned aerial vehicles (UAVs). Specifically, UAVs ensure remote sensing (RS), which offers the advantage of collecting vital information on a large temporal and spatial scale (which cannot be achieved with traditional technologies). However, UAV-based irrigation systems face tremendous challenges due to the various requirements of a powerful computing ability, battery capacity, energy efficiency, and spectral efficiency for different connected devices. This paper addresses the energy efficiency and spectral efficiency trade-off problem of UAV-based irrigation systems. We propose to adopt massive multiple input, multiple output (M-MIMO) technology to ensure wireless communication. In fact, this technology plays a significant role in future sixth-generation (6G) wireless mobile networks and has the potential to enhance the energy efficiency as well as the spectral efficiency. We design a network model with a three-layered architecture and analytically compute the achievable spectral efficiency and the energy efficiency of the studied system. Then, we numerically determine the optimal number of ground base station antennas as well as the optimal number of IoT devices that should be used to ensure the maximum energy efficiency while guaranteeing a high spectral efficiency. The numerical results prove that the proposed UAV-based irrigation system outperforms conventional systems and demonstrate that the best spectral and energy efficiency trade-off is obtained by using the M-MMSE combiner.  
p p  
the fact that most Saudi regions suffer from a desert climate and a meager precipitation rate. Consequently, it is hard to achieve sustainability goals with traditional farming methods. To deal with such challenges, smart farming, also called precision agriculture or Agriculture 5.0, is one of the main pillars of modern society and is considered as a key solution to guarantee food safety and food security [2]. Precision agriculture represents the adoption of new technologies to strengthen the efficiency of a bio-based economy while conserving scarce natural resources. Specifically, smart farming is growing thanks to the adoption of new technologies, including artificial intelligence (AI), the Internet of Things (IoT), and 5G/6G networks [3; 4; 5]. This can assist farmers in taking appropriate measures at the appropriate moment by monitoring soil moisture, temperature, and other environmental factors, consequently making the production process more scientific in terms of fertilization, pest control, and improving crop yields.  
In the paper, we introduce an overview of the literature on precision agriculture with a focus on smart irrigation systems. We present a review regarding the deployment of 5G/6G in precision agriculture, the M-MIMO technology as a keystone of 5G/6G networks, and precise irrigation systems.