Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userEffects of 3D Antenna Radiation and Two-Hop Relaying on Optimal UAV Trajectory in Cellular Networks
81
0
0.0
(
0
)
Added by
Md Moin Uddin Chowdhury
Publication date
2019
fields
Electronic Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
In this paper, considering an interference limited inband downlink cellular network, we study the effects of scheduling criteria, mobility constraints, path loss models, backhaul constraints, and 3D antenna radiation pattern on trajectory optimization problem of an unmanned aerial vehicle (UAV). In particular, we consider a UAV that is tasked to travel between two locations within a given amount of time (e.g., for delivery or surveillance purposes), and we consider that such a UAV can be used to improve cellular connectivity of mobile users by serving as a relay for the terrestrial network. As the optimization problem is hard to solve numerically, we explore the dynamic programming (DP) technique for finding the optimum UAV trajectory. We utilize capacity and coverage performance of the terrestrial network while studying all the effects of different techniques and phenomenon. Extensive simulations show that the maximum sum-rate trajectory provides the best per user capacity whereas, the optimal proportional fair (PF) rate trajectory provides higher coverage probability than the other two. Since, the generated trajectories are infeasible for the UAV to follow exactly as it can not take sharp turns due to kinematic constraints, we generate smooth trajectory using Bezier curves. Our results show that the cellular capacity using the Bezier curves is close to the capacity observed when using the optimal trajectories.
rate research
Read More
This paper explores the effects of three-dimensional (3D) antenna radiation pattern and backhaul constraint on optimal 3D path planning problem of an unmanned aerial vehicle (UAV), in interference prevalent downlink cellular networks. We consider a cellular-connected UAV that is tasked to travel between two locations within a fixed time and it can be used to improve the cellular connectivity of ground users by acting as a relay. Since the antenna gain of a cellular base station changes significantly with the UAV altitude, the UAV can increase the signal quality in its backhaul link by changing its height over the course of its mission. This problem is non-convex and thus, we explore the dynamic programming technique to solve it. We show that the 3D optimal paths can introduce significant network performance gain over the trajectories with fixed UAV heights.
Cellular-connected unmanned aerial vehicles (UAVs) are recently getting significant attention due to various practical use cases, e.g., surveillance, data gathering, purchase delivery, among other applications. Since UAVs are low power nodes, energy and spectral efficient communication is of paramount importance. To that end, multiple access (MA) schemes can play an important role in achieving high energy efficiency and spectral efficiency. In this work, we introduce rate-splitting MA (RSMA) and non-orthogonal MA (NOMA) schemes in a cellular-connected UAV network. In particular, we investigate the energy efficiency of the RSMA and NOMA schemes in a millimeter wave (mmWave) downlink transmission scenario. Furthermore, we optimize precoding vectors of both the schemes by explicitly taking into account the 3GPP antenna propagation patterns. The numerical results for this realistic transmission scheme indicate that RSMA is superior to NOMA in terms of overall energy efficiency.
An integrated access and backhaul (IAB) network architecture can enable flexible and fast deployment of next-generation cellular networks. However, mutual interference between access and backhaul links, small inter-site distance and spatial dynamics of user distribution pose major challenges in the practical deployment of IAB networks. To tackle these problems, we leverage the flying capabilities of unmanned aerial vehicles (UAVs) as hovering IAB-nodes and propose an interference management algorithm to maximize the overall sum rate of the IAB network. In particular, we jointly optimize the user and base station associations, the downlink power allocations for access and backhaul transmissions, and the spatial configurations of UAVs. We consider two spatial configuration modes of UAVs: distributed UAVs and drone antenna array (DAA), and show how they are intertwined with the spatial distribution of ground users. Our numerical results show that the proposed algorithm achieves an average of $2.9times$ and $6.7times$ gains in the received downlink signal-to-interference-plus-noise ratio (SINR) and overall network sum rate, respectively. Finally, the numerical results reveal that UAVs cannot only be used for coverage improvement but also for capacity boosting in IAB cellular networks.
Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the network performance and coverage in wireless communication. However, due to the limitation of their on-board power and flight time, it is challenging to obtain an optimal resource allocation scheme for the UAV-assisted Internet of Things (IoT). In this paper, we design a new UAV-assisted IoT systems relying on the shortest flight path of the UAVs while maximising the amount of data collected from IoT devices. Then, a deep reinforcement learning-based technique is conceived for finding the optimal trajectory and throughput in a specific coverage area. After training, the UAV has the ability to autonomously collect all the data from user nodes at a significant total sum-rate improvement while minimising the associated resources used. Numerical results are provided to highlight how our techniques strike a balance between the throughput attained, trajectory, and the time spent. More explicitly, we characterise the attainable performance in terms of the UAV trajectory, the expected reward and the total sum-rate.
This paper investigates the impact of the channel state information (CSI) and antenna correlation at the multi-antenna relay on the performance of wireless powered dual-hop amplify-and-forward relaying systems. Depending on the available CSI at the relay, two different scenarios are considered, namely, instantaneous CSI and statistical CSI where the relay has access only to the antenna correlation matrix. Adopting the power-splitting architecture, we present a detailed performance study for both cases. Closed-form analytical expressions are derived for the outage probability and ergodic capacity. In addition, simple high signal-to-noise ratio (SNR) outage approximations are obtained. Our results show that, antenna correlation itself does not affect the achievable diversity order, the availability of CSI at the relay determines the achievable diversity order. Full diversity order can be achieved with instantaneous CSI, while only a diversity order of one can be achieved with statistical CSI. In addition, the transmit antenna correlation and receive antenna correlation exhibit different impact on the ergodic capacity. Moreover, the impact of antenna correlation on the ergodic capacity also depends heavily on the available CSI and operating SNR.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
