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It is proven that the scattering, reflection, and refraction properties of electromagnetic signals can be adapted and managed by using reconfigurable intelligent surfaces (RISs). In this paper, we have investigated the performance of a single-input-single-output (SISO) wideband system in terms of achievable data rate by optimizing the phases of RIS elements and performing a fair power allocation for each subcarrier over the entire bandwidth. A new beamforming codebook is developed from which the maximizing signal-to-noise (SNR) configuration is selected. The channel state information (CSI) along with the selected maximizing SNR configuration is then used by the proposed power algorithm to obtain the optimal configuration of the RIS. To validate our proposed method, it is compared with state-of-the-art semidefinite relaxation (SDR) scheme in terms of performance, complexity and run-time consumption. Our method shows dramatically lower computational complexity than the SDR method and achieves an order of 2.5 increase in the achievable data rate with an optimized RIS compared with an un-configured surface. [ABSTRACT FROM AUTHOR]

Using reconfigurable intelligent surfaces (RISs) to improve the coverage and the data rate of future wireless networks is a viable option. These surfaces are constituted of a significant number of passive and nearly passive components that interact with incident signals in a smart way, such as by reflecting them, to increase the wireless system's performance as a result of which the notion of a smart radio environment comes to fruition. In this survey, a study review of RIS‐assisted wireless communication is supplied starting with the principles of RIS which include the hardware architecture, the control mechanisms, and the discussions of previously held views about the channel model and pathloss; then the performance analysis considering different performance parameters, analytical approaches and metrics are presented to describe the RIS‐assisted wireless network performance improvements. Despite its enormous promise, RIS confronts new hurdles in integrating into wireless networks efficiently due to its passive nature. Consequently, the channel estimation for, both full and nearly passive RIS and the RIS deployments are compared under various wireless communication models and for single and multi‐users. Lastly, the challenges and potential future study areas for the RIS aided wireless communication systems are proposed. [ABSTRACT FROM AUTHOR]

Describing the processes leading to deforestation is essential for the development and implementation of the forest policies. In this work, two different learning models were developed in order to identify the best possible model for the assessment of the deforestation causes and trends. We developed autoregressive integrated moving average (ARIMA) model and long short-term memory (LSTM) independently in order to see the trend between tree cover loss and carbon dioxide emission. This study includes the twenty-year data of Pakistan on tree cover loss and carbon emission from the Global Forest Watch (GFW) platform, a known platform to get numerical data. Minimum mean absolute error (MAE) for the prediction of tree cover loss and carbon emission obtained through ARIMA model is 0.89 and 0.95, respectively. The minimum MAE given by LSTM model is 0.33 and 0.43, respectively. There is no such kind of study conducted in order to identify the increase in carbon emission due to tree cover loss most specifically in Pakistan. The results endorsed that one of the main causes of increase in the pollution in the environment in terms of carbon emission is due to tree cover loss. [ABSTRACT FROM AUTHOR]

A rigorous analysis of the concept of coupling manipulation utilizing two antennas suited to modern smartphone devices in talk position for voice calls is presented. By using the optimum relative phase between the elements, they can substantially reduce the specific absorption rate (SAR) but still maintain efficiency due to the splitting of power between them and by exploiting a suitable level of interelement coupling. The same antenna elements can still be used for multiple-input–multiple-output (MIMO) when not in talk position without heavily degrading their fundamental capacity limit, but this is of secondary importance. The concept could be applied to frequency ranges used in mobile communications from 1.8 to 6 GHz where the ground plane has sufficient form factor. Extensive simulations using two planar inverted-F antennas (PIFAs) operating at 2.4 GHz are carried out to demonstrate conceptually how two antennas can be optimized to reduce SAR by over 50% compared to a single antenna element. SAR reduction is maintained regardless of the user’s head composition and how they are handling the device in a talk position. Antenna prototypes are measured and compared to verify the capacity when the handset is used away from the body with two MIMO terminal antennas. [ABSTRACT FROM AUTHOR]

The densification of wireless infrastructure to meet ever-increasing quality of service (QoS) demands, and the ever-growing number of wireless devices may lead to higher levels of electromagnetic field (EMF) exposure in the environment, in the 5G era. The possible long term health effects related to the EMF radiation are still an open debate and requires attention. Therefore, in this paper, we propose a novel EMF-aware resource allocation scheme based on the power domain non-orthogonal multiple access (PD-NOMA) and machine learning (ML) technologies for reducing the EMF exposure in the uplink of cellular systems. More specifically, we use the K-means approach (an unsupervised ML approach) to create clusters of users to be allocated together and to then strategically group and assign them on the subcarriers, based on their associated channel properties. Finding the best number of clusters in the PD-NOMA environment is a key challenge, and in this paper, we have used the elbow method in conjunction with the F-test method to effectively control the maximum number of users to be allocated at the same time per subcarrier. We have also derived an EMF-aware power allocation by formulating and solving a convex optimization problem. Based on the simulation results, our proposed ML-based strategy effectively reduces the EMF exposure, in comparison with the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

The rapid rise of heterogeneous data traffic exposes the shortcomings of fifth-generation (5G) technology, which was initially designed to form self-organizing and self-sustaining networks to facilitate the adoption of the Internet-of-Everything (IoE). This study presents the applications and service requirements of future communication networks. This study details flexible design agreements of the Medium Access Control (MAC) layer of Beyond-5G (B5G) from the current 3rd Generation Partnership (3GPP) study and highlights the current open research issues and challenges which are yet to be optimized. To ensure that the network is self-sustaining and self-organized for B5G paradigm, an intelligent network design is required. Artificial Intelligence (AI) is revolutionizing every aspect of life, therefore, this article provides an overview of how AI plays an important role in improving future-generation communication by solving MAC-related issues. [Display omitted] • This article presents in detail the new vertical, their applications, and requirements of beyond-5G and 6G communication. • This article provides in detail the issues raised by structural changes in the frame of New Radio and presents the open research challenges. • This article presents how artificial intelligence can be used to provide a self-sustainable and self-organizable network by resolving open research problems. • This article provides future research directions in Beyond-5G and 6G networks. [ABSTRACT FROM AUTHOR]

The increasing popularity of using wireless devices to handle routine tasks has increased the demand for incorporating multiple-input-multiple-output (MIMO) technology to utilize limited bandwidth efficiently. The presence of comparatively large space at the base station (BS) makes it straightforward to exploit the MIMO technology's useful properties. From a mobile handset point of view, and limited space at the mobile handset, complex procedures are required to increase the number of active antenna elements. In this paper, to address such type of issues, a four-element MIMO dual band, dual diversity, dipole antenna has been proposed for 5G-enabled handsets. The proposed antenna design relies on space diversity as well as pattern diversity to provide an acceptable MIMO performance. The proposed dipole antenna simultaneously operates at 3.6 and 4.7 sub-6 GHz bands. The usefulness of the proposed 4 × 4 MIMO dipole antenna has been verified by comparing the simulated and measured results using a fabricated version of the proposed antenna. A specific absorption rate (SAR) analysis has been carried out using CST Voxel (a heterogeneous biological human head) model, which shows maximum SAR value for 10 g of head tissue is well below the permitted value of 2.0 W/kg. The total efficiency of each antenna element in this structure is −2.88, −3.12, −1.92 and −2.45 dB at 3.6 GHz, while at 4.7 GHz are −1.61, −2.19, −1.72 and −1.18 dB respectively. The isolation, envelope correlation coefficient (ECC) between the adjacent ports and the loss in capacity is below the standard margin, making the structure appropriate for MIMO applications. The effect of handgrip and the housing box on the total antenna efficiency is analyzed, and only 5% variation is observed, which results from careful placement of antenna elements. [ABSTRACT FROM AUTHOR]

In the past decades, unmanned aerial vehicles (UAVs), also known as drones, have drawn more attention in the academic domain and exploration in the research fields of wireless sensor networks (WSNs). Moreover, applications of drones aid operations related to military support, agriculture industry, and smart Internet-of-Things (IoT). Currently, the use of drone based IoT, also known as Internet-of-Drones (IoD), and their design challenges and techniques are being probed by researchers around the globe. The placement of drones (nodes) is an important consideration in a IoD environment and is closely related to the properties of IoT. Given a base station (BS), sensor nodes (SNs) and IoT devices are designed to capture the signals transmitted by the BS and make use of internet connectivity in a manner to facilitate users. Mutual benefit can be achieved by integrating drones into IoT. The drone based cluster models are not free from challenges. Routing protocols have to be substantiated by key algorithms. Drones are designed to be specific to applications, but the underlying principles are the same. Optimization algorithms are the gateway to better accuracy, performance, and reliability. This article discusses some of these optimization algorithms, include genetic algorithm (GA), bee optimization algorithm, and Chicken Swarm Optimization Clustering Algorithm (CSOCA). Finally, the routing schemes, protocols, and challenges in the context of IoD are discussed. [ABSTRACT FROM AUTHOR]