Reliable and Secure Drone-assisted MillimeterWave Communications

The next generation of mobile networks and wireless communication, including the fifth-generation (5G) and beyond, will provide a high data rate as one of its fundamental requirements. Providing high data rates can be accomplished through communication over high-frequency bands such as the Millimeter-Wave(mmWave) one. However, mmWave communication experiences short-range communication, which impacts the overall network connectivity. Improving network connectivity can be accomplished through deploying Unmanned Ariel Vehicles(UAVs), commonly known as drones, which serve as aerial small-cell base stations. Moreover, drone deployment is of special interest in recovering network connectivity in the aftermath of disasters. Despite the potential advantages, drone-assisted networks can be more vulnerable to security attacks, given their limited capabilities. This security vulnerability is especially true in the aftermath of a disaster where security measures could be at their lowest. This thesis focuses on drone-assisted mmWave communication networks with their potential to provide reliable communication in terms of higher network connectivity measures, higher total network data rate, and lower end-to-end delay. Equally important, this thesis focuses on proposing and developing security measures needed for drone-assisted networks’ secure operation. More specifically, we aim to employ a swarm of drones to have more connection, reliability, and secure communication over the mmWave band. Finally, we target both the cellular 5Gnetwork and Ad hoc IEEE802.11ad/ay in typical network deployments as well as in post-disaster circumstances

Effectiveness of Reconfigurable Intelligent Surfaces to Enhance Connectivity in UAV Networks

Reconfigurable intelligent surfaces (RISs) are expected to make future 6G networks more connected and resilient against node failures, due to their ability to introduce controllable phase-shifts onto impinging electromagnetic waves and impose link redundancy. Meanwhile, unmanned aerial vehicles (UAVs) are prone to failure due to limited energy, random failures, or targeted failures, which causes network disintegration that results in information delivery loss. In this paper, we show that the integration between UAVs and RISs for improving network connectivity is crucial. We utilize RISs to provide path diversity and alternative connectivity options for information flow from user equipments (UEs) to less critical UAVs by adding more links to the network, thereby making the network more resilient and connected. To that end, we first define the criticality of UAV nodes, which reflects the importance of some nodes over other nodes. We then employ the algebraic connectivity metric, which is adjusted by the reflected links of the RISs and their criticality weights, to formulate the problem of maximizing the network connectivity. Such problem is a computationally expensive combinatorial optimization. To tackle this problem, we propose a relaxation method such that the discrete scheduling constraint of the problem is relaxed and becomes continuous. Leveraging this, we propose two efficient solutions, namely semi-definite programming (SDP) optimization and perturbation heuristic, which both solve the problem in polynomial time. For the perturbation heuristic, we derive the lower and upper bounds of the algebraic connectivity obtained by adding new links to the network. Finally, we corroborate the effectiveness of the proposed solutions through extensive simulation experiments.Comment: 14 pages, 8 figures, journal paper. arXiv admin note: text overlap with arXiv:2308.0467