![]() This algorithm navigates the flying robot toward the farthest target dynamically, using the estimated robot–target distances from the received signal strength, until the maximum robot–target distance cannot be further reduced. Because it may be difficult to obtain the locations in practice, such as in Global Navigation Satellite Systems (GNSS) dined environments, a range-based navigation algorithm based on the sliding mode control method is proposed. ![]() The studied problem can be formulated as the conventional smallest circle problem if all the targets’ locations are given. In particular, the problem of finding the optimal position for the flying robot such that all the targets can be monitored by the on-board ground facing camera is considered. In this paper, we focus on a scenario of a flying robot monitoring a set of targets, which are assumed to be moving as a group, to which the sparse distribution of the targets is not applicable. ![]() Finally, we identify related challenges and open issues and shed light on future research directions.įlying robots, also known as drones and unmanned aerial vehicles (UAVs), have found numerous applications in civilian domains thanks to their excellent mobility and reduced cost. Next, we present our vision of a cross-layer architecture that leverages both PLS and blockchain in 5G/xG networks. We begin by providing a thorough discussion about the potential of PLS and blockchain for 5G/xG systems. Then, for the first time, we present a framework for the integration of PLS with blockchain in 5G/xG systems. Motivated by these technological advancements, this paper provides an in-depth review of the existing literature on PLS and blockchain. By exploiting the characteristics of wireless links, PLS can enhance the security of wireless communications, while blockchain can guarantee the decentralization, integrity, and trustworthiness of networks. Within this context, physical layer security (PLS) and blockchain represent promising solutions to complement existing methods. Therefore, 5G/xG networks must consider smarter and more efficient security techniques to operate seamlessly and efficiently. However, due to the emergence of novel computing paradigms, such as quantum computing, traditional security approaches are no longer sufficient to protect over-the-air communications. Typically, networks rely on encryption techniques at higher layers to ensure security and privacy. In addition, the heterogeneity of these networks raises security concerns, particularly, confidentiality, privacy, and trustworthiness. However, the deployment of these technologies poses several challenges, including the lack of network transparency, management decentralization, and reliability. Disruptive technologies, such as massive multiple-input multiple-output, millimeter wave, and multiple access are being deployed to meet these requirements. P>Fifth-generation and beyond (5G and xG) wireless networks are envisioned to meet the requirements of various vertical applications that require higher traffic throughput, ultra-massive connectivity, extremely low latency, and high quality of service. The constant movement of the drones also help reduce the total number of drones required to cover the macro hotspot. These improvements can be realized regardless of users’ and base stations’ density. Via extensive simulations, we demonstrate that the drone base stations moving according to our proposed algorithms can improve the average packet throughput by 82% and the 5th-percentile packet throughput by 430% compared to a baseline scenario, where drones hover over ?xed locations. We consider a practical user association scheme for the moving base stations, which enables user equipments to switch their serving base stations based only on the received signal strength. The constant movement of drones reduces the distance between the base stations and users, which in turn improves the probability of having a line of sight connection. The drone base stations move constantly and update their moving directions following our proposed mobility control algorithm. We study a scenario where multiple drone-mounted base stations cruise freely over a macro hotspot to serve mobile users on the ground.
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