Interference Management in UAV-assisted Integrated Access and Backhaul Networks (original) (raw)
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Access Point Placement for Hybrid UAV-Terrestrial Small-Cell Networks
IEEE Open Journal of the Communications Society, 2021
We address the problem of access point (AP) placement in small-cell networks with partial infrastructure flexibility, i.e., a novel class of problem in Beyond 5G, resultant from the utilization of unmanned aerial vehicles (UAVs) with AP functionalities (UAV-APs), to aid fixed wireless networks in coping with momentary peak-capacity requirements. We use the signal-to-generated-interference-plus-noise ratio (SGINR) metric as an alternative to the traditional signal-to-interference-plus-noise ratio (SINR) to quantify the effects of inter-cell interference (ICI) on the per-user capacity. From average SGINR, we derive the ICI-aware distortion measure leading to the Inter-AP Lloyd algorithm to obtain throughputoptimal AP placement for a fully flexible infrastructure. We then impose a hybridity constraint to the AP placement problem which turns a fraction of the network into a fixed infrastructure composed of terrestrial APs (T-APs) while the remainder is constituted by UAV-APs with flexibility in position. This newly formulated AP placement problem is solved by the proposed Lloyd-type algorithm called Hybrid AP Placement Algorithm (HAPPA). Furthermore, we present an initialization method for the Lloyd and Lloyd-type algorithms for Gaussian mixture models (GMMs) that offers an AP allocation leading to a higher rate compared to the k-means++ initialization. Finally, computer simulations show that the Inter-AP Lloyd algorithm can improve the performance of the worst users by up to 42.75% in achievable rate, assuming a fully flexible network. By using HAPPA on hybrid networks, we achieve improvements of up to 71.92% in sum rate over the fixed network and close the performance gap with fully flexible networks down to 2.02%, when an equal number of UAV-APs and TAPs is used. Further, our proposed initialization scheme always results in a balanced AP allocation, which means a more even distribution of users per AP, whereas the k-means++ scheme results in unbalanced allocations at least 30% of the time, resulting in a worse minimum rate. INDEX TERMS Beyond 5G, hybrid network, inter-cell interference (ICI), Lloyd algorithm, unmanned aerial vehicle (UAV).
Backhaul-Constrained Resource Allocation and 3D Placement for UAV-Enabled Networks
2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 2019
Unmanned aerial vehicle (UAV)-base stations (BS) are envisioned to provide wireless access to areas where the existing wireless infrastructure is either not deployed, damaged or simply congested. In this paper, the problem of minimizing the transmit power of a UAV-BS, while serving users with their QoS requirements and accounting for the wireless backhaul limitation of the UAV, is investigated. To this end, an algorithm that finds the optimal bandwidth assignment in the backhaul link, the optimal 3D position of the UAV, as well as the transmit power distribution in the access and the backhaul links is proposed. Simulation results show that, using the proposed approach, the needed power is greatly reduced, when compared to a strategy that separates between the frequency band used in the access and the backhaul links. In addition, the performance enhancement of a UAV-enabled system over a traditional one in which the MBS directly serves users is shown. Index Terms-UAV-BS, wireless backhaul, in-band full-duplex, QoS requirements.
Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks
ArXiv, 2021
Multi-Unmanned Aerial Vehicle (UAV) Networks is a promising solution to providing wireless coverage to ground users in challenging rural areas (such as Internet of Things (IoT) devices in farmlands), where the traditional cellular networks are sparse or unavailable. A key challenge in such networks is the 3D placement of all UAV base stations such that the formed Multi-UAV Network (i) utilizes a minimum number of UAVs while ensuring – (ii) backhaul connectivity directly (or via other UAVs) to the nearby terrestrial base station, and (iii) wireless coverage to all ground users in the area of operation. This joint Backhaul-and-coverage-aware Drone Deployment (BoaRD) problem is largely unaddressed in the literature, and, thus, is the focus of the paper. We first formulate the BoaRD problem as Integer Linear Programming (ILP). However, the problem is NP-hard, and therefore, we propose a low complexity algorithm with a provable performance guarantee to solve the problem efficiently. Our ...
Interference Management in Ultra-Dense 5G Networks With Excessive Drone Usage
IEEE Access
In fifth generation (5G) networks, the densification of small base stations in the coverage region of macro base station (MBS) leads to significant inter-cell interference (ICI). Similarly, drones (a.k.a. unmanned aerial vehicles) have a diverse scope in multifarious 5G assisted applications and, therefore, cause considerable drones interference (DI) as a result of excessive drone usage. This paper investigates the bottleneck uplink (UL) coverage performance of the MBS edge users in the presence of ICI and DI. To mitigate both ICI and DI, we use an efficient resource allocation scheme known as reverse frequency allocation (RFA). Moreover, we use decoupled association (DeCA) in place of coupled association to further improve UL signal-to-interference ratio. The results depict that RFA in conjunction with DeCA overpass all other techniques in terms of improved UL coverage performance because of effective DI and ICI mitigation.
IEEE Transactions on Network Science and Engineering, 2021
The mushroom growth of cellular users requires novel advancements in the existing cellular infrastructure. One way to handle such a tremendous increase is to densely deploy terrestrial small-cell base stations (TSBSs) with careful management of smart backhaul/fronthaul networks. Nevertheless, terrestrial backhaul hubs significantly suffer from the dense fading environment and are difficult to install in a typical urban environment. Therefore, this paper considers the idea of replacing terrestrial backhaul network with an aerial network consisting of unmanned aerial vehicles (UAVs) to provide the fronthaul connectivity between the TSBSs and the ground core-network (GCN). To this end, we focus on the joint positioning of UAVs and the association of TSBSs such that the sum-rate of the overall system is maximized. In particular, the association problem of TSBSs with UAVs is formulated under communication-related constraints, i.e., bandwidth, number of connections to a UAV, power limit, interference threshold, UAV heights, and backhaul data rate. To meet this joint objective, we take advantage of the genetic algorithm (GA) due to the offline nature of our optimization problem. The performance of the proposed approach is evaluated using the unsupervised learning-based k-means clustering algorithm. We observe that the proposed approach is highly effective to satisfy the requirements of smart fronthaul networks.
A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017
The densification of small-cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small-cell base stations. This involves efficient association and placement of the backhaul hubs that connects these small-cells with the core network. Terrestrial hubs suffer from an inefficient non line of sight link limitations and unavailability of a proper infrastructure in an urban area. Seeing the popularity of flying platforms, we employ here an idea of using networked flying platform (NFP) such as unmanned aerial vehicles (UAVs), drones, unmanned balloons flying at different altitudes, as aerial backhaul hubs. The association problem of these NFP-hubs and small-cell base stations is formulated considering backhaul link and NFP related limitations such as maximum number of supported links and bandwidth. Then, this paper presents an efficient and distributed solution of the designed problem, which performs a greedy search in order to maximize the sum rate of the overall network. A favorable performance is observed via a numerical comparison of our proposed method with optimal exhaustive search algorithm in terms of sum rate and run-time speed.
2018
Addressing the Quality-of-Service (QoS) requirements of users is crucial for service providers to improve the network performance. Furthermore, the transformation from the network-centric to user-centric service paradigm requires service providers to focus on improving the Quality-of-Experience (QoE) which is expected to become an important objective in Next Generation Cellular Networks (NGCNs). Managing QoE is not only a technical issue but also a marketing ability to improve profitability. An efficient strategy to improve the profitability is to apply price differentiation for different service levels. Unmanned Aerial Vehicle Base Stations (UAV-BSs) are envisioned to be an integral component of NGCNs and they create opportunities to enhance the capacity of the network by dynamically moving the supply towards the demand while facilitating services that cannot be provided via other means efficiently. However, building a reliable wireless backhaul link via optimized resource allocati...
Positioning Optimization of UAV (Drones) Base Station in Communication Networks
Malaysian Journal of Fundamental and Applied Sciences
Unmanned aerial vehicles (UAV) and cellular networks are growing closer to being integrated in the realm of wireless communications, which will improve service quality even further. In this study, we investigate a wireless communication system in which two types of base stations—in the air and on the ground—serve separate groups of users. We analyze the effect of the aerial base station (ABS) height and transmit power on the system's downlink and uplink data rates while accounting for the reciprocal interference between the Aerial and terrestrial communication lines. The findings demonstrate that in many cases the best ABS altitude and transmit Power are either the highest or lowest values attainable. The distance between the ABS, the ABS user (AU), and the terrestrial base station user, among other factors, may affect how well they all communicate (TU). In this article we will discuss the following topics: unmanned aerial vehicle (UAV), terrestrial base station (BTS), transmit ...
Full-Duplex and Backhaul-Constrained UAV-Enabled Networks Using NOMA
IEEE Transactions on Vehicular Technology, 2020
In this paper, a full-duplex unmanned aerial vehicle-(UAV) base station is used to provide wireless communication to an area lacking a conventional terrestrial infrastructure, and its efficient deployment is investigated. More concretely, the UAV positioning and resource allocation problems are solved with the aim of minimizing the transmit power of the UAV, while serving users with their rate requirements and accounting for the backhaul limitation of the UAV. To this end, a complete solution for the optimal 3D position of the UAV, the bandwidth assignment and the transmit power distribution in the access and backhaul links is proposed that accounts for both the backhaul interference and the self-interference. When the UAV power budget is insufficient to fulfill rate requirements, nonorthogonal multiple access (NOMA) pairing is conducted to enhance system performance. Simulation results show that, when using the proposed approach, both the achieved sum rate and the percentage of satisfied users are significantly increased, when compared to a strategy that uses separate frequency bands in the access and backhaul links, as well as to a previously proposed method. Index Terms-UAV-BS, wireless backhaul, in-band full-duplex, QoS requirements, NOMA. I. INTRODUCTION When used as flying base stations (BS), unmanned aerial vehicles (UAV) can help increase the throughput and the coverage of traditional communication systems thanks to their mobility, flexibility and low cost [1]. Moreover, they can help alleviate traffic congestion in hotspot areas and establish communication links in remote and disaster areas, where the communication infrastructure is either non-existent or damaged [2]. Therefore, their use in wireless communication systems has received a lot of attention in recent literature [3]. In [4], the authors investigated the optimal location of the UAV to minimize its transmit power. The optimal UAV altitude that maximizes its coverage region was evaluated in [5]. In [6], the authors built on the results of [5] and found the 3D location of the UAV that maximizes the coverage for users having different quality-of service (QoS) requirements. Contrary to most terrestrial BSs, UAVs are connected to the core network through a wireless backhaul link [2], which was not accounted for in the works of [4]-[6]. That said, to reap the benefits promised by the use of UAV-BSs, this backhaul