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1. UAV-Based in-band Integrated Access and Backhaul for 5G Communications

   Fouda, Abdurrahman; Ibrahim, Ahmed S; Guvenc, Ismail; Ghosh, Monisha (October 2018, IEEE Vehicular Technology Conference (VTC2018-Fall))

   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. 

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2. Optimal Path Construction with Decode and Forward Relays in mmWave Backhaul Networks

   https://doi.org/10.1109/ICNC47757.2020.9049696  

   Yan, Yan; Hu, Qiang; Blough, Douglas M. (February 2020, Proceedings of the International Conference on Computing, Networking and Communications)

   In this paper, we consider the problem of constructing paths using decode and forward (DF) relays for millimeter wave (mmWave) backhaul communications in urban environments. Due to the large number of obstacles in urban environments, line-of-sight (LoS) wireless links, which are necessary for backhaul communication, often do not exist between small-cell base stations. To address this, some earlier works proposed creating multi-hop paths that use mmWave relay nodes with LoS communication between every pair of consecutive nodes to form logical links between base stations. We present algorithms, based on a novel widest-path formulation of the problem, for selecting decode and forward relay node locations in such paths. Our main algorithm is the first polynomial-time algorithm that constructs a relay path with a throughput that is proven to be the maximum possible. We also present variations of this algorithm for constrained problems in which: 1) each possible relay location can host only one relay node, and 2) minimizing the number of hops in the relay path is also an objective. For all of the proposed algorithms, the achievable throughput and numbers of relays are evaluated through simulation based on a 3-D model of a section of downtown Atlanta. The results show that, over a large number of random cases, our algorithm can always find paths with very high throughput using a small number of relays. We also compare and contrast the results with our earlier work that studied the use of amplify-and-forward (AF) relays for the same scenario. 

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3. End-to-end Simulation of mmWave Out-of-band Backhaul Networks in ns-3

   https://doi.org/https://doi.org/10.1145/3337941.3337943  

   Hu, Qiang; Liu, Yuchen; Yan, Yan; Blough, Douglas M. (January 2019, Proceedings of the 2019 Workshop on Next-Generation Wireless with ns-3)

   In this paper, we focus on the end-to-end simulation of millimeter-wave (mmWave) out-of-band backhaul networks in ns-3. We first introduce a design for an out-of-band backhaul module in ns-3. A custom backhaul network device is proposed that can be added to nodes to enable out-of-band backhaul transmissions. Since the new backhaul module is still under development, we extended the existing mmWave integrated-access-and-backhaul (IAB) module to enable mmWave out-of-band backhaul simulation and produce some preliminary results on throughput performance. We also modified the existing scheduler in the IAB module to support customizable scheduling for logical links in out-of-band backhaul networks. We used the customizable scheduler to implement an optimal scheduling algorithm from prior work and demonstrate that it increases throughput performance by up to 40% in certain scenarios. 

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4. On the Feasibility of High Throughput mmWave Backhaul Networks in Urban Areas

   https://doi.org/10.1109/ICNC47757.2020.9049824  

   Hu, Qiang; Blough, Douglas M. (February 2020, Proceedings of the International Conference on Computing, Networking and Communications)

   In this paper, we investigate the design of high throughput relay-assisted millimeter-wave (mmWave) backhaul networks in urban areas. Different from most related works, we consider the deployment of dedicated simple mmWave relay devices to help enhance the line-of-sight (LoS) connectivity of the backhaul network in urban areas with abundant obstacles. Given a set of (logical) backhaul links between base stations in the network, we propose an algorithm to find high-throughput LoS paths with relays for all logical links by minimizing interference within and between paths. We also propose methods to modify the backhaul topology to increase the probability of finding high-throughput paths using our algorithm. Extensive simulations, based on a 3-D model of a section of downtown Atlanta, demonstrate that high-throughput topologies, with minimal inter-path and intra-path interference, are feasible in most cases. The analyses also yield some insights on the mmWave backhaul network design problem. 

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5. Distributed Cooperative Spectrum Sharing in UAV Networks Using Multi-Agent Reinforcement Learning

   https://doi.org/10.1109/CCNC.2019.8651796  

   Shamsoshoara, Alireza; Khaledi, Mehrdad; Afghah, Fatemeh; Razi, Abolfazl; Ashdown, Jonathan (February 2019, 16th IEEE Annual Consumer Communications & Networking Conference (CCNC))

   In this paper, we develop a distributed mechanism for spectrum sharing among a network of unmanned aerial vehicles (UAV) and licensed terrestrial networks. This method can provide a practical solution for situations where the UAV network may need external spectrum when dealing with congested spectrum or need to change its operational frequency due to security threats. Here we study a scenario where the UAV network performs a remote sensing mission. In this model, the UAVs are categorized to two clusters of relaying and sensing UAVs. The relay UAVs provide a relaying service for a licensed network to obtain spectrum access for the rest of UAVs that perform the sensing task. We develop a distributed mechanism in which the UAVs locally decide whether they need to participate in relaying or sensing considering the fact that communications among UAVs may not be feasible or reliable. The UAVs learn the optimal task allocation using a distributed reinforcement learning algorithm. Convergence of the algorithm is discussed and simulation results are presented for different scenarios to verify the convergence. 

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