The sixth generation (6G) wireless communication network presents itself as a promising technique that can be utilized to provide a fully data-driven network evaluating and optimizing the end-to-end behavior and big volumes of a real-time network within a data rate of Tb/s. In addition, 6G adopts an average of 1000+ massive number of connections per person in one decade (2030 virtually instantaneously). The data-driven network is a novel service paradigm that offers a new application for the future of 6G wireless communication and network architecture. It enables ultra-reliable and low latency communication (URLLC) enhancing information transmission up to around 1 Tb/s data rate while achieving a 0.1 millisecond transmission latency. The main limitation of this technique is the computational power available for distributing with big data and greatly designed artificial neural networks. The work carried out in this paper aims to highlight improvements to the multi-level architecture by enabling artificial intelligence (AI) in URLLC providing a new technique in designing wireless networks. This is done through the application of learning, predicting, and decision-making to manage the stream of individuals trained by big data. The secondary aim of this research paper is to improve a multi-level architecture. This enables user level for device intelligence, cell level for edge intelligence, and cloud intelligence for URLLC. The improvement mainly depends on using the training process in unsupervised learning by developing data-driven resource management. In addition, improving a multi-level architecture for URLLC through deep learning (DL) would facilitate the creation of a data-driven AI system, 6G networks for intelligent devices, and technologies based on an effective learning capability. These investigational problems are essential in addressing the requirements in the creation of future smart networks. Moreover, this work provides further ideas on several research gaps between DL and 6G that are up-to-date unknown.

This letter presents a high-isolation dual-band multiple-input multiple-output (MIMO) antenna based on the ground plane modification and optimized metamaterials (MMs) for 5G millimeter-wave applications. The antenna is a monopole providing a dual-band response at 5G 28/38 bands with a small physical size (4.8 × 2.9 × 0.762 mm ³ , excluding the feeding line). The MIMO consists of two symmetric radiating elements arranged adjacently with the mutual coupling of −19 dB and −17 dB at 28 and 38 GHz, respectively. Reducing the ground length enhances the isolation to 34.6 dB at 28 GHz, whereas embedding the MMs diminishes the coupling to −47 dB at 38 GHz. The trust-region gradient-based search algorithm is employed to optimize the MM structure dimensions and to enhance the isolation at 38 GHz. The MMs also contribute to the enhancement of bandwidth from 1.6 GHz to 1.7 GHz at 28 GHz (27.1–28.8 GHz) and from 2.75 GHz to 3.7 GHz at 38 GHz (35.2–38.9 GHz). The proposed system is capable of covering both 28/38 bands with low profile structure, high isolation, low envelope correlation coefficient (ECC) ( $\lt 0.2 \cdot 10^{-4}$ ), and high diversity gain (DG) (>9.99 dB). These properties demonstrate the system applicability for 5G millimeter-wave cellular communications.

Metamaterials (MTMs) are artificially engineered materials with unique electromagnetic properties not occurring in natural materials. MTMs have gained considerable attention owing to their exotic electromagnetic characteristics such as negative permittivity and permeability, thereby a negative refraction index. These extraordinary properties enable many practical applications such as super-lenses, and cloaking technology, and are used to design different electromagnetic devices like filters, polarization converters, sensors, and absorbers. Advances in MTMs have made new application fields to emerge in communication subsystems, especially in the field of antennas. MTMs are usually arranged in front or above the radiating element, or incorporated in the same substrate to improve the performance of planar antennas, in terms of improving directivity, gain, bandwidth, and efficiency, reducing the size and mutual coupling, and deflecting the radiation characteristics. High gain antennas are demanded in modern wireless communication systems. Their importance is in improving the signal strength by reducing the interference and alleviating the free space path loss. This review paper provides a brief introduction to MTMs, with the focus on their operating principles. Furthermore, a detailed study of antenna gain enhancement based on the various properties of MTMs is carried out. MTMs with low values of constitutive parameters; zero-index material (ZIM), low-index material (LIM), epsilon-near-zero (ENZ), and mu-near-zero (MNZ) are discussed in detail in the context of their capability to enhance the gain of a broad class of planar antennas. The low impedance property and lensing property, which is achieved by three different characteristics: high refractive index (HRI), gradient refractive index (GRIN), and negative refractive index (NRI) materials, are loaded to planar antennas for gain enhancement. The scope of this review has been limited to antennas that were experimentally validated in the respective source papers.

In this research, a reconfigurable metamaterial (MM) structure was designed using a millimeter-wave (MMW) band with two configurations that exhibit different refractive indices. These two MM configurations are used to guide the antenna’s main beam in the desired direction in the 5th generation (5G) band of 28 GHz. The different refractive indices of the two MM configurations created phase change for the electromagnetic (EM) wave of the antenna, which deflected the main beam. A contiguous squares resonator (CSR) is proposed as an MM structure to operate at MMW band. The CSR is reconfigured using three switches to achieve two MM configurations with different refractive indices. The simulation results of the proposed antenna loaded by MM unit cells demonstrate that the radiation beam is deflected by angles of +30° and −27° in the E-plane, depending on the arrangement of the two MM configurations on the antenna substrate. Furthermore, these deflections are accompanied by gain enhancements of 1.9 dB (26.7%) and 1.5 dB (22.4%) for the positive and negative deflections, respectively. The reflection coefficients of the MM antenna are kept below −10 dB for both deflection angles at 28 GHz. The MM antennas are manufactured and measured to validate the simulated results.

Metamaterials (MMs) are synthetic composite structures with superior properties not found in naturally occurring materials. MMs have gained massive attention over the last two decades because of their extraordinary properties, such as negative permittivity and permeability. These materials enable many applications in communication subsystems, especially in the field of antenna design, to enhance gain, bandwidth, and efficiency, reduce the size, and deflect the radiation pattern. The demand for beam-deflection antennas is significant in modern wireless communication research studies due to their importance in enhancing service quality, system security, avoiding interference, and economizing power. The MM structures are usually included in the vicinity of the radiating element or incorporated in the antenna substrate for controlling the radiation pattern. This review study provides an introduction to MMs, focusing on their electromagnetic properties, classification, and design approaches. Furthermore, a detailed study of using the MMs to manipulate the radiation is carried out, where different properties such as the positive/negative refractive index, epsilon-near-zero (ENZ), and mu near-zero (MNZ) are employed to achieve a beam-deflection antenna. Reconfigurable MMs are also loaded to the antenna to achieve multi-directional beam deflection with negligible effect on the antenna’s physical size. Moreover, the gradient-index (GRIN) based on MMs is used to obtain high deflection angles with minor effects on other antenna properties.