In recent years, unmanned aerial vehicles (UAVs) have received considerable attention from regulators, industry and research community, due to rapid growth in a broad range of applications. Particularly, UAVs are being used to provide a promising solution to reliable and cost-effective wireless communications from the sky. The deployment of UAVs has been regarded as an alternative complement of existing cellular systems, to achieve higher transmission efficiency with enhanced coverage and capacity. However, heavily utilized microwave spectrum bands below 6 GHz utilized by legacy wireless systems are insufficient to attain remarkable data rate enhancement for numerous emerging applications. To resolve the spectrum crunch crisis and satisfy the requirements of 5G and beyond mobile communications, one potential solution is to use the abundance of unoccupied bandwidth available at millimeter wave (mmWave) frequencies. Inspired by the technique potentials, mmWave communications have also paved the way into the widespread use of UAVs to assist wireless networks for future 5G and beyond wireless applications. In this paper, we provide a comprehensive survey on current achievements in the integration of 5G mmWave communications into UAV-assisted wireless networks. More precisely, a taxonomy to classify the existing research issues is presented, by considering seven cutting-edge solutions. Subsequently, we provide a brief overview of 5G mmWave communications for UAV-assisted wireless networks from two aspects, i.e., key technical advantages and challenges as well as potential applications. Based on the proposed taxonomy, we further discuss in detail the state-of-the-art issues, solutions, and open challenges for this newly emerging area. Lastly, we complete this survey by pointing out open issues and shedding new light on future directions for further research on this area.

/pdf/a-survey-on-5g-millimeter-wave-communications-for-uav-1ex6lnjkdj.pdf

A Survey on 5G Millimeter Wave Communications for UAV-Assisted Wireless Networks

Densification of network base stations is indispensable to achieve the stringent Quality of Service (QoS) requirements of future mobile networks. However, with a dense deployment of transmitters, interference management becomes an arduous task. To solve this issue, exploring radically new network architectures with intelligent coordination and cooperation capabilities is crucial. This survey paper investigates the emerging user-centric cell-free massive multiple-input multiple-output (MIMO) network architecture that sets a foundation for future mobile networks. Such networks use a dense deployment of distributed units (DUs) to serve users; the crucial difference from the traditional cellular paradigm is that a specific serving cluster of DUs is defined for each user. This framework provides macro diversity, power efficiency, interference management, and robust connectivity. Most importantly, the user-centric approach eliminates cell edges, thus contributing to uniform coverage and performance for users across the network area. We present here a guide to the key challenges facing the deployment of this network scheme and contemplate the solutions being proposed for the main bottlenecks facing cell-free communications. Specifically, we survey the literature targeting the fronthaul, then we scan the details of the channel estimation required, resource allocation, delay, and scalability issues. Furthermore, we highlight some technologies that can provide a management platform for this scheme such as distributed software-defined network (SDN) and self-organizing network (SON). Our article serves as a check point that delineates the current status and indicates future directions for this area in a comprehensive manner.

User-centric Cell-free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions.

Densification of network base stations is indispensable to achieve the stringent Quality of Service (QoS) requirements of future mobile networks. However, with a dense deployment of transmitters, interference management becomes an arduous task. To solve this issue, exploring radically new network architectures with intelligent coordination and cooperation capabilities is crucial. This survey paper investigates the emerging user-centric cell-free massive Multiple-input multiple-output (MIMO) network architecture that sets a foundation for future mobile networks. Such networks use a dense deployment of distributed units (DUs) to serve users; the crucial difference from the traditional cellular paradigm is that a specific serving cluster of DUs is defined for each user. This framework provides macro diversity, power efficiency, interference management, and robust connectivity. Most importantly, the user-centric approach eliminates cell edges, thus contributing to uniform coverage and performance for users across the network area. We present here a guide to the key challenges facing the deployment of this network scheme and contemplate the solutions being proposed for the main bottlenecks facing cell-free communications. Specifically, we survey the literature targeting the fronthaul, then we scan the details of the channel estimation required, resource allocation, delay, and scalability issues. Furthermore, we highlight some technologies that can provide a management platform for this scheme such as distributed software-defined network (SDN). Our article serves as a check point that delineates the current status and indicates future directions for this area in a comprehensive manner. 

/pdf/user-centric-cell-free-massive-mimo-networks-a-survey-of-1awg5gqq.pdf

User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions

In this paper, we characterize the performance of several canonical mobility models in a drone cellular network in which drone base stations (DBSs) serve a set of user equipment (UE) on the ground. In particular, we consider the following four mobility models: (i) straight line (SL), (ii) random stop (RS), (iii) random walk (RW), and (iv) random waypoint (RWP), among which the SL mobility model is inspired by the simulation models used by the third generation partnership project (3GPP) for the placement and trajectory of drones, while the other three are well-known canonical models (or their variants) that offer a useful balance between realism and tractability. Assuming the nearest-neighbor association policy, we consider two service models for the UEs: (i) UE independent model (UIM), and (ii) UE dependent model (UDM). While the serving DBS follows the same mobility model as the other DBSs in the UIM, it is assumed to fly towards the UE of interest in the UDM and hover above its location after reaching there. The main contribution of this paper is a unified approach to characterize the point process of DBSs for all the mobility and service models. Using this, we provide exact mathematical expressions for the average received rate and the session rate as seen by the typical UE. Further, using tools from the calculus of variations, we concretely demonstrate that the simple SL mobility model provides a lower bound on the performance of other general mobility models (including the ones in which drones follow curved trajectories) as long as the movement of each drone in these models is independent and identically distributed (i.i.d.). To the best of our knowledge, this is the first work that provides a rigorous analysis of key canonical mobility models for an infinite drone cellular network and establishes useful connections between them.

Performance Characterization of Canonical Mobility Models in Drone Cellular Networks

In this paper, we establish a foundation for the multi-layer aerial networks (MANs), which are modeled as $K$ layer aerial networks (ANs), where each layer has unmanned aerial vehicles (UAVs) with different densities, floating altitudes, and transmission power. To make the framework applicable for various scenarios in MAN, we consider the transmitter- and the receiver-oriented node association rules as well as the air-to-ground and air-to-air channel models, which form line of sight links with a location-dependent probability. We then newly analyze the association probability, the main link distance distribution, successful transmission probability (STP), and area spectral efficiency (ASE) of MAN. The upper bounds of the optimal densities that maximize STP and ASE are also provided. Finally, in the numerical results, we show the optimal UAV densities of each AN that maximize the ASE and the STP decrease with the altitude of the network. We also show that when the total UAV density is fixed for two layer AN, the use of single layer in higher(lower) altitude only for all UAVs can achieve better performance for low(high) total density case. Otherwise, distributing UAVs in two layers, i.e., MAN, achieves better performance.

Multi-layer Unmanned Aerial Vehicle Networks: Modeling and Performance Analysis

Since various types of unmanned aerial vehicles (UAVs) with different hardware capabilities are introduced, we establish a foundation for the multi-layer aerial network (MAN). First, the MAN is modeled as K layer ANs, and each layer has UAVs with different densities, floating altitudes, and transmission power. To make the framework applicable for various scenarios in MAN, we consider the transmitter- and the receiver-oriented node association rules as well as the air-to-ground and air-to-air channel models, which form line of sight links with a location-dependent probability. We then newly analyze the association probability, the main link distance distribution, successful transmission probability (STP), and area spectral efficiency (ASE) of MAN. The upper bounds of the optimal densities that maximize STP and ASE are also provided. Finally, in the numerical results, we show the optimal UAV densities of an AN that maximize the ASE and the STP decrease with the altitude of the network. We also show that when the total UAV density is fixed for two layer AN, the use of single layer in higher(lower) altitude only for all UAVs can achieve better performance for low(high) total density case, otherwise, distributing UAVs in two layers, i.e., MAN, achieves better performance.

In this paper, we consider a relative received link power (RRLP)-based coordinated multi-point (CoMP) joint transmission (JT) in the multi-tier ultra-dense networks (UDN). In this CoMP scheme, we identify the cooperating base stations (BSs) by comparing the average received link power (ARLP) of the neighbouring BSs with respect to the BS having the strongest ARLP (i.e., the main link BS) to a user. To analyze the performance of this CoMP scheme in the downlink multi-tier UDN, we first approximate the received signal power distribution, and derive the coverage probability using stochastic geometry. After revisiting the area spectral efficiency (ASE) to make it more suitable for CoMP transmission in UDN, we also analyze the ASE and the network energy efficiency (NEE). Using simulations, we validate the derived coverage probability, and investigate the CoMP performance in multi-tier UDN. Our simulations show that the RRLP-based CoMP scheme can outperform the fixed number of strongest BS-based CoMP scheme in the high BS density regime. Our study of the NEE performance reveals that not only the RRLP-based CoMP scheme is more efficient than conventional non-CoMP transmission scenario, but also its NEE performance improves with the average number of cooperating BSs.

Base Station Coordination Scheme for Multi-Tier Ultra-Dense Networks

In this paper, we provide the model of the multi-layer aerial network (MAN), composed unmanned aerial vehicles (UAVs) that distributed in Poisson point process (PPP) with different transmission power, heights, and densities. In our model, we consider the line of sight (LoS) and non-line of sight (NLoS) channels, which is probabilistically formed. We first derive the probability distribution function (PDF) of the main link distance and the Laplace transform of interference of MAN by considering a transmitter/receiver association based on the strongest average received power. We then analyze the successful transmission probability (STP) of the MAN, and provide the upper bounds of the optimal UAV densities in each layer that maximize the STP of the MAN. Through the numerical results, we show the existence of the optimal height of the aerial network (AN) after exploring the performance tradeoff caused by the height. We also show both the optimal UAV density as well as its upper bound decrease with the height of the ANs.

Performance Analysis for Multi-Layer Unmanned Aerial Vehicle Networks

In this paper, we propose a novel coordinated multipoint (CoMP) downlink transmission strategy for the ultra-dense network (UDN) environment. In this proposed CoMP transmission scheme, we exploit the average received link power (ARLP) of the base stations (BSs) with respect to the ARLP of the strongest BS to a typical user, to dynamically adjust the number of cooperating BSs serving that user in the network. This allows us to effectively manage the inter-cell interference in the UDN regime. Our numerical results and simulations show that the proposed scheme can out-perform the existing fixed number of BS based CoMP transmission scheme in the high BS density scenario.

Dongsun Kim

Papers

Multi-layer Unmanned Aerial Vehicle Networks: Modeling and Performance Analysis

Multi-layer Unmanned Aerial Vehicle Networks: Modeling and Performance Analysis

Base Station Coordination Scheme for Multi-Tier Ultra-Dense Networks

Performance Analysis for Multi-Layer Unmanned Aerial Vehicle Networks

A Novel Coordinated Multi-point Downlink Transmission Scheme for Ultra-dense Networks