As large enterprises and data-centres embrace agile workflows by the implementation of virtualisation and cloud technologies, they demand greater flexibility of the underlying infrastructure. Conventional Internet Protocol (IP) networks have proven adequate in the past, but fail to offer rapid configuration and programmability features due to their bundled data and control planes. Software Defined Networking (SDN) is aimed to address this issue with a centralised controlled architecture. In this paper, we first explore SDN products currently available in the market, followed by a critical analysis of SDN implementation, and comparison with existing network technologies. This leads to a summary of the implications surrounding SDN encompassing cost, security, and reliability.

Abstract Unmanned aerial vehicles (UAVs), also known as drones, have gained significant attention in recent years due to a wide range of military as well as civilian applications. Due to high mobility, flying at different altitudes and in different environments, their design, structure, size, weight, connectivity, coverage, communication, and various other factors are of critical importance. UAV communication systems should be able to incorporate seamless connectivity, wide coverage, high-quality signal, and operation over a wide range of frequencies. Thus, antennas are critical to enhance received signal quality and to extend UAV coverage. Reconfigurable Intelligent Surfaces (RISs) and antennas have drawn significant attention recently due to their enormous potential in wireless communication systems and have been widely studied for UAVs too. This paper presents a comprehensive survey of reconfigurable intelligent surfaces and antennas and their deployment in UAVs. It also presents a critical analysis and evaluation of the research work conducted on reconfigurable antennas in UAVs. Challenges and future research directions have also been presented. Lastly, some significant UAV applications and prospects of UAV-based communication combined with modern technologies have been discussed.

Unmanned aerial vehicle (UAV)-assisted communication is becoming a streamlined technology in providing improved coverage to the internet-of-things (IoT) based devices. Rapid deployment, portability, and flexibility are some of the fundamental characteristics of UAVs, which make them ideal for effectively managing emergency-based IoT applications. This paper studies a UAV-assisted wireless IoT network relying on non-orthogonal multiple access (NOMA) to facilitate uplink connectivity for devices spread over a disaster region. The UAV setup is capable of relaying the information to the cellular base station (BS) using decode and forward relay protocol. By jointly utilizing the concepts of unsupervised machine learning (ML) and solving the resulting non-convex problem, we can maximize the total energy efficiency (EE) of IoT devices spread over a disaster region. Our proposed approach uses a combination of k-medoids and Silhouette analysis to perform resource allocation, whereas, power optimization is performed using iterative methods. In comparison to the exhaustive search method, our proposed scheme solves the EE maximization problem with much lower complexity and at the same time improves the overall energy consumption of the IoT devices. Moreover, in comparison to a modified version of greedy algorithm, our proposed approach improves the total EE of the system by $19 \%$ for a fixed 50 k target number of bits.

The research investigates the data rates of a wide-band multi-user system by optimizing the phases of the reconfigurable intelligent surfaces (RISs) elements and performing fair power allocation for subcarriers. A practical beamforming codebook is developed to select the RIS configuration that maximizes the signal-to-noise ratio (SNR). This guides the iterative power and semidefinite relaxation (SDR) algorithms for finding the optimal RIS configuration. The iterative power method is validated by comparing the achievable data rate and the computational complexity with the existing techniques in the literature. Simulation results revealed that the data rate performance of our proposed iterative power method is comparatively close to the well-known approaches such as the SDR and the strongest tap maximization (STM). Notably, our method exhibits superior performance to STM in non-line-of-sight (NLoS) channels, while also maintaining lower computational complexity compared to SDR.

Deforestation poses a significant global environmental challenge with far-reaching consequences for biodiversity, climate change, and livelihoods. In this context, applying advanced technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) holds immense promise. This paper aims to comprehensively review and analyze the role of IoT, AI, and remote sensing technologies in monitoring, detecting, predicting, and preventing deforestation. By providing real-time data and enabling early detection, these technologies contribute to addressing activities like illegal logging, plant diseases, and forest fires. This review presents an overview of the advantages and limitations of these technologies, accompanied by an analysis of their current state and future potential. Key technologies covered include IoT, satellite imagery, drones, and AI algorithms, with each offering unique applications. Importantly, this paper underscores the significance of these technologies in protecting forests and the diverse species they support. The findings discussed herein aim to inform ongoing debates and provide a foundation for further research in this crucial domain. Ultimately, the knowledge gained from this research has the potential to guide practical interventions and policies for effective forest conservation.

The detection of changes in land cover and land use (LCLU) is crucial for various geospatial applications, including urban development and environmental management. One vital aspect of LCLU research involves identifying modifications in impervious surface cover, which has significantly increased due to global economic growth and the rising urban population in many parts of the world. This investigation employs Landsat 9 OLI- 2/TIRS-2 imagery with a 30m spatial resolution to map structures in the Ziarat District of Pakistan, encompassing forests, water bodies, and barren land. It aims to detect changes in tree cover and canopy height. A time series of Landsat 9 OLI-2/TIRS-2 images were utilized to create change detection and land cover maps. The Analysis of Land Cover and Land Use (LCLU) for the Ziarat District was conducted using the GEE platform. The satellite images were classified into broad land cover classes, which include impervious surfaces, forest/tree cover, grassland/cropland, and water. The generated change detection map facilitates the identification of locations that have undergone modifications due to new constructions, offering valuable insights for the implementation of urban development policies and disaster management on a global scale.

The primary means of communication is quickly evolving to be wireless communications. However, when compared to wired links, their properties render traffic susceptible to time and location-dependent signal attenuation, noise, fading, and interference, resulting in time variable channel capacity and link error rate. Scheduling algorithms are critical in wireless connections for ensuring quality of service (QoS) metrics such as throughput, latency, jitter, fairness, and packet loss rate. The scheduler is critical in current and future cellular communications because it assigns resource blocks (RB) to different users for transmission. The scheduling algorithm decides based on the link state, number of sessions, reserved rates, and the status of the session queues. The information required by a scheduler implemented in the base station can be easily gathered from the downlink stream. It evaluates the performance of four well-known scheduling methods, including round robin (RR), best channel quality indicator (BCQI), proportional fair (PF), and fractional frequency reuse (FFR), for dynamic use Pedestrian (PedA) and Vehicular (VehA). The performance of these four algorithms is measured in terms of throughput, fairness index, spectral efficiency, and overall effectiveness. System-level simulations were carried out utilizing a MATLAB-based LTE-A Vienna simulator.

In wireless communications, various study findings have shown that a reconfigurable intelligent surface (RIS) may successfully alter wireless wave parameters like phase and amplitude without requiring sophisticated signal processing and decoding at the receiver. However, it is necessary to take into account designing the surface under a realistic frequency selective fading channel. Because of this, we chose a wideband OFDM multi-user communication system based on an actual RIS setup that considers mutual coupling (MC) and electromagnetic interference (EMI). We used Hadamard matrix in the pilot transmissions to estimate the uncontrollable and the controllable channels. The best pilot configuration was selected to initialize the gradient descent method in order to calculate the optimal reflection coefficient that maximize the data rate for each user in the presence of EMI and MC. Simulation results revealed that the data rate has been degraded when considering EMI and MC for around 30 Mbits/s for each user. This confirms that both EMI and MC must be given considerable attention in our research due to their inevitable effects on the system performance.

Abstract 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.

Industry 4.0 and 5.0 are paradigms of digitalization and intelligentization. The huge available bandwidth and the least spectral interference in the millimeter-wave (mmWave) band can pave the way for a wide range of new industrial automation capabilities. Sophisticated industrial applications such as industrial Internet of Things, time-sensitive networking (TSN), intelligent logistics, product tracking, remote visual monitoring and surveillance, image-guided automated assembly and automatic fault detection require high bandwidth, reliability and low latency which can be ensured using the mmWave band. In this paper, we address the physical layer (PHY) requirements of industrial communication from the viewpoint of Industry 4.0 and beyond, while highlighting the key performance indicators. This paper proposes a 60 GHz mmWave antenna system with high reliability and low latency, making it ideally suited for industrial IoT and communication. The proposed novel antenna system is designed to cover the entire 9 GHz bandwidth of the 60 GHz standard spectrum (57 to 66 GHz) with a single element peak gain of 8.2 dBi. It provides high gain and efficiency across all four channels of 60 GHz communication from 57.24 GHz to 65.88 GHz, each channel with 2.16 GHz of bandwidth. Moreover, the simulated achieved beamforming gain of the proposed antenna system reaches 16.1 dBi, which satisfies the high gain requirement for 60 GHz multi-gigabit industrial communication. The proposed antenna system is a promising physical layer candidate suitable for communication standards such as WiGig IEEE802.11ay, IEEE802.11ad, IEEE802.15.3c, ECMA-387 and WirelessHD to ensure multi-gigabit wireless communication at 60 GHz ISM band for factory automation and industrial applications.

In the last decade, a sharp surge in the number of user proximity wireless devices (UPWDs) has been observed. This has increased the level of electromagnetic field (EMF) exposure of the users substantially and hence, the possible physiological effects. Ambient backscatter communications (ABC) has appeared to be a promising solution to reduce the power consumption of UPWDs by converting ambient radio frequency (RF) signals into useful signals while non-orthogonal multiple access (NOMA) is a compelling multiplexing scheme for enhanced spectral efficiency. This paper utilises a novel combination of ABC and NOMA to reduce the EMF in the uplink of wireless communication systems. This contemporary approach of EMF-aware resource optimization is based on k-medoids and Silhouette analysis. To curtail the uplink EMF, a power allocation strategy is also derived by converting a non-convex problem to a convex one and solving accordingly. The numerical results exhibit that the proposed ABC, NOMA, and unsupervised learning based scheme achieves a reduction in the EMF by at least 75% in comparison to the existing solutions.

Since the inception of Henry Ford’s “production line” in 1913, continuous efforts have been made to enhance the efficiency of motor manufacture. Recently, a shift to Industry 4.0 has resulted in the digitisation of traditional production systems, by integration of specialist software applications. Concurrently, there have been efforts to develop and produce connected vehicles, with aspirations of autonomous features in the distant future. Achieving these concepts relies on the implementation of wireless communication media, such as 5G Vehicle-to-Everything (V2X) which is interoperable in the shop floor environment, and in the public realm. We review the key use-cases for 5G V2X in the context of motor factories, and how they can be used with private 5G networks, which leads to the development of the term “Vehicle-to-Factory” (V2F). Based on this information, we explore the feasibility of a vehicle transitioning from a private 5G network to the public 5G network after its manufacture. Furthermore, we proceed to identify challenges which arise from the implementation of 5G, and explore novel approaches to overcome these, such as infrastructure sharing which uses existing street furniture to provide 5G coverage.

Identity-based attacks serve as the basis of an intruder's attempt to launch security infringements in mobile health monitoring scenarios. Wireless channel perturbations due to the presence of human body are a relative phenomenon depending heavily on the subject's dielectric properties. A new body-centric signature authorization (B-CSAI) approach based on time-frequency domain characteristics was proposed. This method utilizes multiple millimeter wave bands of 27-28 GHz, 29-30 GHz, and 31-32 GHz, thereby enhancing the security in body-centric communications exploiting benefits of subject specific channel signature. The proposed bornprint method is based on the intrinsic identity-related time-frequency domain information, which generated by the user's natural hand motion signature and resulting creeping waves and space waves. It can meet the unconditional keyless authorization requirements. A detailed measurement campaign considering radiation efficiency (ñ(dB) = -25.8, -24.7, -26.4), path-loss exponent, and shadowing factor in three millimeter wave bands, using six human subjects confirm the usability and efficiency of the proposed approach. This also shows that there is a wide space for realizing security from physical mechanisms.

Increasing prevalence of dementia has posed several challenges for care-givers. Patients suffering from dementia often display wandering behavior due to boredom or memory loss. It is considered to be one of the challenging conditions to manage and understand. Traits of dementia patients can compromise their safety causing serious injuries. This paper presents investigation into the design and evaluation of wandering scenarios with patients suffering from dementia using an S-band sensing technique. This frequency band is the wireless channel commonly used to monitor and characterize different scenarios including random, lapping, and pacing movements in an indoor environment. Wandering patterns are characterized depending on the received amplitude and phase information of that measures the disturbance caused in the ideal radio signal. A secondary analysis using support vector machine is used to classify the three patterns. The results show that the proposed technique carries high classification accuracy up to 90% and has good potential for healthcare applications.

This paper presents a dual‐band coplanar waveguide (CPW) fed printed antenna with rectangular shape design blocks having ultrawideband characteristics, proposed and implemented on an FR4 substrate. The size of the proposed antenna is just 25 mm × 35 mm. A novel rounded corners technique is used to enhance not only the impedance bandwidth but also the gain of the antenna. The proposed antenna design covers two ultrawide bands which include 1.1–2.7 GHz and 3.15–3.65 GHz, thus covering 2.4 GHz Bluetooth/Wi‐Fi band and most of the bands of 3G, 4G, and a future expected 5G band, that is, 3.4–3.6 GHz. Being a very low‐profile antenna makes it very suitable for the future 5G Internet of Things (IoT) portable applications. A step‐by‐step design process is carried out to obtain an optimized design for good impedance matching in the two bands. The current densities and the reflection coefficients at different stages of the design process are plotted and discussed to get a good insight into the final proposed antenna design. This antenna exhibits stable radiation patterns on both planes, having low cross polarization and low back lobes with a maximum gain of 8.9 dB. The measurements are found to be in good accordance with the simulated results.

A novel frequency reconfigurable microstrip patch antenna has been presented for 3.6 GHz and 5 GHz. Compared to the traditional, complicated and high cost frequency reconfigurable antennas, our work is featured by a simple and concise design. The frequency reconfiguration is obtained by using layers of mercury and liquid crystal polymer (LCP) on conventional patch antenna. The proposed structure was modelled and simulated using CST Microwave Studio. The antenna was first simulated in free space to check the antenna parameters such as return loss, gain, radiation pattern and efficiency. After obtaining the results, the antenna was simulated for analysing the on-body performance by using numerical model of human body. The simulated return loss for both the configurations is less than -10 dB at the radiating frequencies. The free space simulated results show the close agreement with the on-body test results.

Body-centric wireless networks are used for connectivity between on-body and on-off body communications for various applications for rescue, diagnostics and medical usage. Multiple features of modern portable and wearable devices necessitate antenna operation at a number of frequencies. A compact, low profile and multi-band antenna is presented for body-centric wireless networks in this study. The conventional microstrip rectangular patch antenna has been converted into a multi-band antenna by using layers of mercury and liquid crystal polymer (LCP). The antenna performance in free space and in body-mounted configurations are evaluated and compared using computer simulations. The proposed antenna supports six frequencies for operation at ISM/Wi-Fi/C band. A minimal shift in the operating frequencies while operating in on-body configuration makes this the proposed antenna very resilient to frequency de-tuning caused by the human body presence. The antenna also offers high peak gain values (>7.68 dBi) in the two configurations at all of the operating frequencies.