# Ultra-Wideband Antenna Design for 5G NR Using the Bezier Search Differential Evolution Algorithm
## 1 Introduction  
A significant aspect of emerging Internet of Things (IoT) technologies is low-powered sensor networks and the effort to achieve self-sustainability in both rural and urban environments. With the introduction of 5G-and-Beyond technologies, in cases such as smart cities, the availability of ambient RF (RadioFrequency) energy is vastly increased, making it a perfect source for green energy applications. To collect this type of energy, dedicated compact devices, called rectennas, are used. In the meantime, great effort is made in the domain of machine learning, regarding optimization methods and, specifically, evolutionary algorithms, as they provide an efficient way of finding the optimal solution in complex but well-parameterized problems. Lately, a huge scientific effort has been put into proposing new rectenna designs with a variety of applications, characteristics, and frequency bands that they collect energy from, as well as optimizing one of its components, i.e., the antenna. In [1], a cutting-edge rectenna with ultra-wideband features is proposed that efficiently harvests energy from frequencies ranging between 1.7 and 2.7 GHz. This covers bands used by technologies such as that of GSM at 1.8 GHz, UMTS at 2.1 GHz, Wi-Fi at 2.4 GHz, and LTE at 2.6 GHz. In [2] the antenna component of this rectenna is optimized in order to refine the design by reducing its degrees of freedom while preserving its wideband performance. In the present research effort, the goal is to broaden the bandwidth of the initial antenna to include 5G New Radio (frequency range 3.3-3.7 GHz), and if possible, to further simplify the design by reducing its degrees of freedom, making it a suitable solution for most low-power self-sustainable sensor networks, both in rural and urban scenarios. Thus, the research problem can be defined as designing a multi-band rectenna that operates in several popular frequency bands like that of GSM at 1.8 GHz, UMTS at 2.1 GHz, Wi-Fi at 2.4 GHz, and LTE at 2.6 GHz and the 5G NR FR1 band at 3.5 GHz. We used the CST Studio Suite for antenna simulations, which is a high-performance full-wave commercial software. In order to perform the optimization process, a CST-Matlab Wrapper was designed by the authors, which contained all the functions to manipulate a CST antenna design, using a corresponding Matlab script. Furthermore, a variety of optimization methods were studied, including evolutionary algorithms, which were tested on several benchmarks, resulting in the Bezier Search Differential Evolution Algorithm (BeSD) [3] as a suitable algorithm for increase in antenna bandwidth. The goal of the optimization process was achieved by providing an antenna that fulfills all the aforementioned goals, both increasing the operation bandwidth and simplifying the design as much as possible, while presenting all the other important characteristics for the harvesting of RF energy. Specifically, the operation bandwidth of the antenna is extended to include 5G NR at 3.5 GHz, starting from 1.4 GHz to 3.9 GHz, also enabling technologies around 1.5 GHz that are suitable for mid-range high-speed communications. Meanwhile, it is still capable of harvesting RF energy from all technologies supported by the initial design, namely that of GSM at 1.8 GHz, UMTS at 2.1 GHz, Wi-Fi at 2.4 GHz, and LTE at 2.6 GHz. Last but not least, the optimization process leads to reduction in design complexity by discarding all structural parameters or modifications that are unnecessary for the goal to be achieved, resulting in a simple, compact, and robust design of a circular antenna with a stub extension on it that operates in all the bands of the vastly used technologies.