# A Review of Multifunctional Antenna Designs for Internet of Things
## 1 Introduction
For instance, durable antennas are essential for use in harsh environmental conditions (e.g., agricultural fields), whereas biomedical applications may require antennas that are more flexible and efficient to be placed in a patient and immersed in the highly lossy human body [4]. In scenarios requiring high data throughput, antennas capable of wideband, dual-band, or even multi-band operation become critical. For 5G and future generations where space-division multiple access (SDMA) is utilized, antennas with reconfigurable radiation patterns that can produce non-overlapping multi-beams while operating within a specific communication protocol are prioritized [5]. Additionally, the EM link may need to exhibit different polarizations, such as linear and circular-elliptical (right- or left-hand rotating). This feature calls for multi-polarized IoT antennas to allow parallel simultaneous propagation of orthogonal signals, increasing the communication capacity. These situations underscore the need to develop novel antennas or re-engineer existing ones to enhance the designer's toolkit. The goal is to accommodate a broader range of applications while also enabling precise adjustments to optimize critical performance indicators of the antenna. In recent years, a growing number of innovative antenna designs have been introduced in the academic literature, targeting one or more of the above objectives to ensure their compatibility with IoT devices. Various methods are employed in the design and optimization of these antennas, including characteristic mode analysis [6; 7], full-wave solvers [8], equivalent circuits [9], and analytical solutions [10]. Currently, the most common approach involves using numerical full-wave electromagnetic or multiphysics solvers. This process starts with a basic antenna structure, such as a rectangular patch antenna, which is then modified through the addition of slots, new elements, or even a complete redesign [11]. Subsequently, parametric or optimization methods are applied to fine-tune the antenna's performance to meet specific operational criteria. Once the design is finalized, a prototype is manufactured and tested under small-signal conditions to evaluate its S-parameters, radiation pattern, and efficiency [8]. The effectiveness of an antenna is typically assessed based on its size, bandwidth, axial ratio (for circularly polarized antennas), reconfigurability, and manufacturability. Recent reviews on IoT antennas classify them based on attributes such as reconfigurable properties [12], design methodology [8], type [13], bandwidth [14], and the kinds of tunable elements utilized [15]. Occasionally, review papers introduce new metrics to facilitate a more equitable comparison among different antenna designs. One such metric, the axial-to-impedance bandwidth ratio, was proposed to evaluate an antenna's capability to function as circularly polarized (CP) throughout its entire operational bandwidth [15]. This metric and similar others aim to quantify the performance and suitability of antennas for specific applications. The term \"IoT\" includes a wide range of applications, each with its unique requirements, making it overly simplistic to presuppose that any IoT antenna is suitable for all IoT applications. When an antenna is identified as suitable for IoT, it is essential to specify its operational domain. For instance, a wideband, high-gain, and beamforming-capable antenna might be ideal for IoT applications in 5G networks but less suitable for others [4]. Therefore, comparing IoT antennas across different applications without considering their specific operational contexts is impractical. To address this issue, we undertake a comprehensive review of IoT antennas, categorizing them based on their field of operation within IoT. This approach requires selecting the most representative categories of IoT applications, considering the unique nature of each application and the specific antenna characteristics it demands.