Search

The integration of cellular connectivity in drones signifies a crucial leap forward, offering the potential to revolutionize multiple industries. This comprehensive review examines the latest developments in the field of machine learning based handover (HO) decision-making for connected drones in future networks. The paper reviews a spectrum of machine learning techniques and evaluates their effectiveness in drones’ HO, exploring avenues such as hybrid AI models that combine the strengths of different ML approaches. Notably, combining deep reinforcement learning with other techniques forms promising solutions. The review finds that deep reinforcement learning models, when integrated with other techniques such as dueling double deep Q-network, have shown promising results in realizing optimized HO decisions and improving overall reliability. Additionally, the paper addresses prevalent research challenges, including issues related to high mobility, the three-dimensional nature of drone flight, small-cell deployment, and integration into cellular networks, emphasizing the importance of innovative solutions to achieve a more efficient and seamless handover process. By considering these obstacles and offering a forward-looking perspective outlining potential research directions, the review contributes to guiding future advancements in drones’ HO decision-making, ultimately facilitating the realization of more efficient and reliable drone operations and unlocking the full potential of drone connectivity and mobility within future networks.

A new adaptive frequency selective surface (AFSS) has been presented for electromagnetic (EM) shielding applications. Passive EM shields lack reconfigurability which severely limits their application. Moreover, active EM shields involving PIN diodes and other active elements consume power all the time. This paper incorporates a novel adaptive approach with frequency selective surface (FSS) to create a smart environment. The unit cell of the designed FSS has the shape of an octagon loop; each loop includes a pin diode at 180° intervals. An envelope detector has been used to trigger the microcontroller whenever an incident RF signal has been detected. The PIN diodes are switched ON or OFF automatically based on the requirements using a microcontroller to save power. When the PIN diodes are OFF, the FSS is in the shielding mode and when they are ON it is in the transmission mode. A prototype has been built for measurements. A good agreement between theory and experiment has been observed. The proposed AFSS can also be programmed as a time-based event and remote-controlled for on-demand EM wave shielding applications.

Textile antennas are currently being researched and developed so that they can be integrated into clothing. In this paper, two textile antennas with cotton and silk substrate are presented. The antennas operate at GPS L1 frequency, which is 1.575 GHz. This paper discusses the effect of antenna parameters on free space and on-body conditions, and the effect of antenna bending. Based on simulation and measurement results, the parameter values obtained indicate that the antenna can operate properly at a frequency of 1.575 GHz and is safe to use on the body.

Flood is a natural disaster caused by the rise of water levels, typically in urban areas. This phenomenon can cause damages to properties such as buildings and landscapes. Moreover, it also can cause death among humans and animals. Malaysia is among the country that has rainfall throughout the years alongside monsoon seasons. Therefore, this country is prone to floods that are not predictable that causes the public to be unprepared to face potential floods. Although the authorities have taken some measures, such as the installation of the monitoring system, it is not efficient, expensive, and difficult to maintain. Hence, this study aims to design a low-cost flood monitoring system comprising a rainfall sensor, temperature sensor, humidity sensor, controller (Arduino), and GSM modem. The system will monitor the rainfall rates alongside temperature and humidity in deciding for the potential occurrence of flood. The data will be sent to a host PC with Graphical User Interface via GSM modem. The developed prototype aims to be installed at a selected location for monitoring and testing.

This paper analyses the impact of 3D multipath in an LTE-Advanced heterogeneous network. The impact of the base station array configuration is considered in both the azimuth and elevation planes. Spatial and temporal multipath statistics are generated for example macro- and picocellular base stations, and these are combined with appropriately oriented complex polarimetric antenna patterns. The resulting wideband channels are then passed to an LTE-Advanced physical layer simulator. The optimal spatial multiplexing mode is determined by computing the throughput using the received bit mutual information rate for all modulation and coding schemes. The fastest link speed for each user is identified given a packet error rate threshold of 10%. Results show that RMS angle spread statistics and the base station MIMO array configuration strongly influence user performance in an LTE-A network. The deployment of macrocellular vertical arrays is shown to significantly degrade network performance. In contrast, the elevation angle spread is found to be far greater in picocells, and this allows vertical arrays to be applied to produce compact high performance picobase stations.