Reconfigurable Intelligent Surface (RIS)-assisted uncrewed Aerial Vehicle (UAV) communications have been realized as essential to space-air-group system integration in the 6 G technology landscape. Trajectory planning plays a crucial role in RIS-assisted UAV communications to face the challenges of UAV’s limited power capacities and dynamic wireless channels. Existing solutions assume complete channel state information, focus on single-rotor UAVs, and rely heavily on time-consuming training processes for machine learning; thus, they lack applicability to deal with highly dynamic real-world scenarios. To fill these research gaps, we aim to characterize RIS-assisted UAV communications and design responsive and accurate UAV trajectory planning algorithms in this paper. We first develop a communication model with incomplete information and an energy consumption model for quadrotor UAVs. We then formulate UAV trajectory planning as an optimization problem to minimize UAV’s energy consumption while maintaining communication throughput. To solve this problem, we design an acceleration framework, FedX, for reinforcement learning (RL) solvers and present two fast trajectory planning algorithms, FedSAC and FedPPO, as instantiations of the FedX framework. Our evaluation results indicate that the proposed framework is effective and efficient–more than 3 times faster with 5 agents and 7 times faster with 10 agents than standard RL algorithms, making it suitable for using RL solvers within wireless networks and mobile computing environments. We also discuss and identify the pros and cons of our proposed framework.

A social approach can be exploited for the Internet of Things (IoT) to manage a large number of connected objects. These objects operate as autonomous agents to request and provide information and services to users. Establishing trustworthy relationships among the objects greatly improves the effectiveness of node interaction in the social IoT and helps nodes overcome perceptions of uncertainty and risk. However, there are limitations in the existing trust models. In this paper, a comprehensive model of trust is proposed that is tailored to the social IoT. The model includes ingredients such as trustor, trustee, goal, trustworthiness evaluation, decision, action, result, and context. Building on this trust model, we clarify the concept of trust in the social IoT in five aspects such as (1) mutuality of trustor and trustee, (2) inferential transfer of trust, (3) transitivity of trust, (4) trustworthiness update, and (5) trustworthiness affected by dynamic environment. With network connectivities that are from real-world social networks, a series of simulations are conducted to evaluate the performance of the social IoT operated with the proposed trust model. An experimental IoT network is used to further validate the proposed trust model.

A simulation study of the channel capacity of a multiple-input multiple-output (MIMO) antenna system exploiting multiple polarizations is carried out. We focus on a simple yet realistic trimonopole antenna structure, taking into account all the mutual coupling and casing effects using the computational electromagnetics solver-numerical electromagnetics code. Simulation results show that, with a special transmit geometry, using the collocated trimonopole antennas at a size-constrained receiver can offer channel capacity that approaches the capacity of an uncorrelated MIMO Rayleigh channel. In addition, it is shown that the capacity increase is mainly attributed to polarization diversity instead of pattern diversity. Furthermore, we find that the mutual coupling and casing effects in the trimonopole system can actually provide a large capacity increase with less constraint on the antenna configurations than the idealized tridipole system.

A Mobile Ad-Hoc Network (MANET) is a popular type of wireless network that is formed by a collection of mobile nodes. Each node in such network has the capability to communicate with its neighbors and non-neighbors through a wireless medium without using any existing network infrastructure. Due to the lack of infrastructure, all nodes in Ad-Hoc network are designed to act as an end system and a router for other nodes. Traditionally, the dominant design methodology for the network protocols is based on an Open Systems Interconnection (OSI) reference model. This methodology divided the stack into seven layers where each layer operates independently. Due to the dynamics of the Unmanned Aerial Vehicle (UAV) Ad-Hoc network, the layered architecture is not flexible enough to achieve certain quality of services (QoS) required by some applications. To overcome the limitations of the layering technique, cross-layering approach is used in this paper so to adjust some key parameters in the first three layers based on the aircraft attitude variations (pitch, roll and yaw), hence we can enhance the performance of such networks. To that respect, directional antenna is going to be used by the UAVs to extend the coverage area and reduce the number of hops. Meanwhile, we designed a new Medium Access Control (MAC) scheme that adapts its parameters based on the channel bit error rate which is indeed affected by the new antenna system and aircraft attitude. we called this scheme Intelligent Medium Access Control Protocol for Unmanned Aerial Vehicle (IMAC UAV). As for the routing protocol, We developed the Optimized Link State Routing Protocol (OLSR) so that the decision for selecting the route will be based on a local profile that holds the gathered information from the first three layers. Our new scheme is called Directional Optimized Link State Routing Protocol (DOLSR). We proved by OPNET simulator that our proposed techniques gave better end-to-end delay than the IEEE802.11 standard.

Unmanned aerial vehicle (UAV) has been used recently a lot in military applications as well as in civilian. It shows great advantages and importance in the search and rescue, real-time surveillance, reconnaissance operations, traffic monitoring, hazardous site inspection and range extension. Moreover, UAVs are suited for situations that are too dangerous for direct human monitoring. In general, UAVs have the potential to create an ad-hoc network and greatly reduce the hops from source to destination. However, the type of the mission and the capability of the UAV which are determined by its shape and construction causes a lot of networking issues. Most UAVs used in communication networks assumed the use of omni-directional antenna. In this paper, we considered a collection of UAVs that communicate through a wireless link as a mobile ad-hoc network (MANET) using directional antenna. This technique offers tremendous advantages over that of using omni-directional antenna, although it requires an adaptive medium access control (MAC) to adapt the new antenna system as well as the constraint imposed by the UAV. To be more specific, we introduced a new mechanism that is called target information table to work with our new scheme during the switch from omni-directional to directional antenna. We made a comparison between the two techniques using optimized network engineering tool (OPNET). Our results show good improvement for end-to-end delay as well as throughput.