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Register a new userRay Tracing Analysis for UAV-assisted Integrated Access and Backhaul Millimeter Wave Networks
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Added by
Abdurrahman Fouda
Publication date
2019
fields
Electronic Engineering
and research's language is
English
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The use of Millimeter-wave (mmWave) spectrum in cellular communications has recently attracted growing interest to support the expected massive increase in traffic demands. However, the high path-loss at mmWave frequencies poses severe challenges. In this paper, we analyze the potential coverage gains of using unmanned aerial vehicles (UAVs), as hovering relays, in integrated access and backhaul (IAB) mmWave cellular scenarios. Specifically, we utilize the WinProp software package, which employs ray tracing methodology, to study the propagation characteristics of outdoor mmWave channels at 30 and 60 GHz frequency bands in a Manhattan-like environment. In doing so, we propose the implementation of amplify-and-forward (AF) and decode-and-forward (DF) relaying mechanisms in the WinProp software. We show how the 3D deployment of UAVs can be defined based on the coverage ray tracing maps at access and backhaul links. Furthermore, we propose an adaptive UAV transmission power for the AF relaying. We demonstrate, with the aid of ray tracing simulations, the performance gains of the proposed relaying modes in terms of downlink coverage, and the received signal to interference and noise ratio (SINR).
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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.
We introduce the concept of using unmanned aerial vehicles (UAVs) as drone base stations for in-band Integrated Access and Backhaul (IB-IAB) scenarios for 5G networks. We first present a system model for forward link transmissions in an IB-IAB multi-tier drone cellular network. We then investigate the key challenges of this scenario and propose a framework that utilizes the flying capabilities of the UAVs as the main degree of freedom to find the optimal precoder design for the backhaul links, user-base station association, UAV 3D hovering locations, and power allocations. We discuss how the proposed algorithm can be utilized to optimize the network performance in both large and small scales. Finally, we use an exhaustive search-based solution to demonstrate the performance gains that can be achieved from the presented algorithm in terms of the received signal to interference plus noise ratio (SINR) and overall network sum-rate.
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.
The integration of unmanned aerial vehicles (UAVs) and millimeter wave (mmWave) wireless systems has been recently proposed to provide high data rate aerial links for next generation wireless networks. However, establishing UAV-based mmWave links is quite challenging due to the random fluctuations of hovering UAVs which can induce antenna gain mismatch between transmitter and receiver. To assess the benefit of UAV-based mmWave links, in this paper, tractable, closed-form statistical channel models are derived for three UAV communication scenarios: (i) a direct UAV-to-UAV link, (ii) an aerial relay link in which source, relay, and destination are hovering UAVs, and (iii) a relay link in which a hovering UAV connects a ground source to a ground destination. The accuracy of the derived analytical expressions is corroborated by performing Monte-Carlo simulations. Numerical results are then used to study the effect of antenna directivity gain under different channel conditions for establishing reliable UAV-based mmWave links in terms of achieving minimum outage probability. It is shown that the performance of such links is largely dependent on the random fluctuations of hovering UAVs. Moreover, higher antenna directivity gains achieve better performance at low SNR regime. Nevertheless, at the high SNR regime, lower antenna directivity gains result in a more reliable communication link. The developed results can therefore be applied as a benchmark for finding the optimal antenna directivity gain of UAVs under the different levels of instability without resorting to time-consuming simulations.
The deployment of unmanned aerial vehicles (UAVs) is proliferating as they are effective, flexible and cost-efficient devices for a variety of applications ranging from natural disaster recovery to delivery of goods. We investigate a transmission mechanism aiming to improve the data rate between a base station (BS) and a user equipment through deploying multiple relaying UAVs. We consider the effect of interference, which is incurred by the nodes of another established communication network. Our primary goal is to design the 3D trajectories and power allocation for the UAVs to maximize the data flow while the interference constraint is met. The UAVs can reconfigure their locations to evade the unintended/intended interference caused by reckless/smart interferers. We also consider the scenario in which smart jammers chase the UAVs to degrade the communication quality. In this case, we investigate the problem from the perspective of both UAV network and smart jammers. An alternating-maximization approach is proposed to address the joint 3D trajectory design and power allocation problem. We handle the 3D trajectory design by resorting to spectral graph theory and subsequently address the power allocation through convex optimization techniques. Finally, we demonstrate the efficacy of our proposed method through simulations.
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