Communications with spectrum sharing in 5g networks via drone-mounted base stations

The fifth generation wireless network is designed to accommodate enormous traffic demands for the next decade and to satisfy varying quality of service for different users. Drone-mounted base stations (DBSs) characterized by high mobility and low cost intrinsic attributes can be deployed to enhance the network capacity. In-band full-duplex (IBFD) is a promising technology for future wireless communications that can potentially enhance the spectrum efficiency and the throughput capacity. Therefore, the following issues have been identified and investigated in this dissertation in order to achieve high spectrum efficiency and high user quality of service. First, the problem of deploying DBSs is studied. Deploying more DBSs may increase the total throughput of the network but at the expense of the operation cost. The droNe-mounted bAse station PlacEment (NAPE) problem with consideration of IBFD communications and DBS backhaul is then formulated. The objective is to minimize the number of deployed DBSs while maximizing the total throughput of the network by incorporating IBFD-enabled communications for both access links and backhaul links via DBSs as relay nodes. A heuristic algorithm is proposed to solve the NAPE problem, and its performance is evaluated via extensive simulations. Second, the 3-D DBS placement problem is investigated as the communication efficiency is greatly affected by the positions of DBSs. Then, the DBS placement with IBFD communications (DSP-IBFD) problem for downlink communications is formulated, and two heuristic algorithms are proposed to solve the DSP-IBFD problem based on different DBS placement strategies. The performance of the proposed algorithms are demonstrated via extensive simulations. Third, the potential benefits of jointly optimizing the radio resource assignment and 3-D DBS placement are explored, upon which the Drone-mounted Base Station Placement with IBFD communications (DBSP-IBFD) problem is formulated. Since the DBSP-IBFD problem is NP-hard, it is then decomposed into two sub-problems: the joint bandwidth, power allocation and UE association problem and the DBS placement problem. A 1/2(1-/2^{l}})-approximation algorithm is proposed to solve the DBSP-IBFD problem based on the solutions to the two sub-problems, where l is the number of simulation runs. Simulation results demonstrate that the throughput of the proposed approximation algorithm is superior to benchmark algorithms. Fourth, the uplink communications is studied as the mobile users need to transmit and receive data to and from base stations. The Backhaul-aware Uplink communications in a full-duplex DBS-aided HetNet (BUD) problem is investigated with the objective to maximize the total throughput of the network while minimizing the number of deployed DBSs. Since the BUD problem is NP-hard, it is then decomposed into three sub-problems: the joint UE association, power and bandwidth assignment problem, the DBS placement problem and the problem of determining the number of DBSs to be deployed. The AA-BUD algorithm is proposed to solve the BUD problem with guaranteed performance based on the solutions to the three sub-problems, and its performance is demonstrated via extensive simulations. The future work comprises two parts. First, a DBS can be used to provide both communications and computing services to users. Thus, how to minimize the average latency of all users in a DBS-aided mobile edge computing network requires further investigation. Second, the short flying time of a drone limits the deployment and the performance of DBSs. Free space optics (FSO) can be utilized as the backhaul link and the energizer to provision both communication and energy to a DBS. How to optimize the charging efficiency while maximizing the total throughput of the network requires further investigation

Trajectory optimization and resource allocation for UAV base stations under in-band backhaul constraint

The application of unmanned aerial vehicles (UAVs) to emerging communication systems has attracted a lot of research interests due to the advantages of UAVs, such as high mobility, flexible deployment, and cost-effectiveness. The UAV-carried base stations (UAV-BS) can provide on-demand service to users in temporary or emergency events. However, how to optimize the communication performance of a UAV-BS with a limited-bandwidth wireless backhaul is still a challenge. This paper focuses on improving the spectrum efficiency of a UAV-BS while guaranteeing user fairness under in-band backhaul constraint. We propose to maximize the minimum user rate among all the users served by the UAV-BS by jointly optimizing the allocation of bandwidth and transmit power, as well as the trajectory of the UAV-BS. As the formulated problem is non-convex, we propose an efficient algorithm to solve it suboptimally based on the alternating optimization and successive convex optimization methods. Computer simulation results show that the proposed algorithm achieves a significantly higher minimum user rate than the benchmark schemes

Exploiting UAV as NOMA based relay for coverage extension

Unmanned aerial vehicles (UAVs) aided communication has acquired research interest in many civilian and military applications. The use of UAV as base stations and as aerial relays to improve coverage of existing cellular networks is prevalent in current literature. Along with this, a few studies have proposed the use of non-orthogonal multiple access (NOMA) in UAV communications. In this paper, we propose a network where a ground user and an aerial UAV relay is accessed using NOMA, where the UAV acts as decode-and-forward (DF) relay to extend the coverage of source. The performance of the proposed model is shown by evaluating outage behaviour for different transmit power and fading environments with Monte Carlo simulations. System throughput of proposed network appears to be better than orthogonal multiple access (OMA) based equivalent network. The results show that with an adequate height of the UAV NOMA based relay, quality of service (QoS) of cell edge user is satisfactory

Drone-assisted emergency communications

Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area and to fully embody the advantage of drone-assisted communications. In order to retrieve signals from MUs in a large disaster struck area, DBSs need to overcome the large pathloss incurred by the long distance between DBSs and MBSs. This can be addressed by the following two strategies. First, placing multiple drones in a disaster struck area can be used to mitigate the problem of large backhaul pathloss. In this method, data from MUs in the disaster struck area may be forwarded by more than one drone, i.e., DBSs can enable drone-to-drone communications. Thus, the throughput from the disaster struck area can potentially be enhanced by this multi-drone strategy. A cooperative DBS placement and channel allocation algorithm is proposed to maximize the aggregated data rate from MUs in a disaster struck area. It is demonstrated by simulations that the aggregated data rate can be improved by more than 10%, as compared to the scenario without drone-to-drone communications. Second, free space optics (FSO) can be used as backhaul links to reduce the backhaul pathloss. FSO can provision a high-speed point-to-point transmission and is thus suitable for backhaul transmission. A heuristic algorithm is proposed to maximize the number of MUs that can be served by the drones by optimizing user association, DBS placement and spectrum allocation iteratively. It is demonstrated by simulations that the proposed algorithm can cover over 15% more MUs at the expense of less than 5% of the aggregated throughput. Equipping DBSs and MBSs with FSO transceivers incurs extra payload for DBSs, hence shortening the hovering time of DBSs. To prolong the hovering time of a DBS, the FSO beam is deployed to facilitate simultaneous communications and charging. The viability of this concept has been studied by varying the distance between a DBS and an MBS, in which an optimal location of the DBS is found to maximize the data throughput, while the charging power directed to the DBS from the MBS diminishes with the increasing distance between them. Future work is planned to incorporate artificial intelligence to enhance drone-assisted networking for various applications. For example, a drone equipped with a camera can be used to detect victims. By analyzing the captured pictures, the locations of the victims can be estimated by some machine learning based image processing technology

A review of relay network on UAVS for enhanced connectivity

One of the best evolution in technology breakthroughs is the Unmanned Aerial Vehicle (UAV). This aerial system is able to perform the mission in an agile environment and can reach the hard areas to perform the tasks autonomously. UAVs can be used in post-disaster situations to estimate damages, to monitor and to respond to the victims. The Ground Control Station can also provide emergency messages and ad-hoc communication to the Mobile Users of the disaster-stricken community using this network. A wireless network can also extend its communication range using UAV as a relay. Major requirements from such networks are robustness, scalability, energy efficiency and reliability. In general, UAVs are easy to deploy, have Line of Sight options and are flexible in nature. However, their 3D mobility, energy constraints, and deployment environment introduce many challenges. This paper provides a discussion of basic UAV based multi-hop relay network architecture and analyses their benefits, applications, and tradeoffs. Key design considerations and challenges are investigated finding fundamental issues and potential research directions to exploit them. Finally, analytical tools and frameworks for performance optimizations are presented

Positioning of multiple unmanned aerial vehicle base stations in future wireless network

Abstract. Unmanned aerial vehicle (UAV) base stations (BSs) can be a reliable and efficient alternative to full fill the coverage and capacity requirements when the backbone network fails to provide the requirements during temporary events and after disasters. In this thesis, we consider three-dimensional deployment of multiple UAV-BSs in a millimeter-Wave network. Initially, we defined a set of locations for a UAV-BS to be deployed inside a cell, then possible combinations of predefined locations for multiple UAV-BSs are determined and assumed that users have fixed locations. We developed a novel algorithm to find the feasible positions from the predefined locations of multiple UAVs subject to a signal-to-interference-plus-noise ratio (SINR) constraint of every associated user to guarantees the quality-of-service (QoS), UAV-BS’s limited hovering altitude constraint and restricted operating zone because of regulation policies. Further, we take into consideration the millimeter-wave transmission and multi-antenna techniques to generate directional beams to serve the users in a cell. We cast the positioning problem as an ℓ₀ minimization problem. This is a combinatorial, NP-hard, and finding the optimum solution is not tractable by exhaustive search. Therefore, we focused on the sub-optimal algorithm to find a feasible solution. We approximate the ℓ₀ minimization problem as non-combinatorial ℓ₁-norm problem. The simulation results reveal that, with millimeter-wave transmission the positioning of the UAV-BS while satisfying the constrains is feasible. Further, the analysis shows that the proposed algorithm achieves a near-optimal location to deploy multiple UVABS simultaneously

On the performance of a uav-aided wireless network based on nb-iot

In recent years, interest in Unmanned Aerial Vehicles (UAVs) as a means to provide wireless connectivity has substantially increased thanks to their easy, fast and flexible deployment. Among the several possible applications of UAV networks explored by the current literature, they can be efficiently employed to collect Internet-of-Things (IoT) data because the non-stringent latency and small-size traffic type is particularly suited for UAVs’ inherent characteristics. However, the implications coming from the implementation of existing technology in such kinds of nodes are not straightforward. In this article, we consider a Narrow Band IoT (NB-IoT) network served by a UAV base station. Because of the many configurations possible within the NB-IoT standard, such as the access structure and numerology, we thoroughly review the technical aspects that have to be implemented and may be affected by the proposed UAV-aided IoT network. For proper remarks, we investigate the network performance jointly in terms of the number of successful transmissions, access rate, latency, throughput and energy consumption. Then, we compare the obtained results on different and known trajectories in the research community and study the impact of varying UAV parameters such as speed and height. Moreover, the numerical assessment allows us to extend the discussion to the potential implications of this model in different scenarios. Thus, this article summarizes all the main aspects that must be considered in planning NB-IoT networks with UAVs