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Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges
Yong Zeng, Rui Zhang, Teng Joon Lim
TL;DR
UAV-aided wireless communications still face incomplete UAV-ground channel modeling and difficult flight-path optimization. This article surveys the networking architecture, channel characteristics, design considerations, use cases, and mobility-based performance techniques, concluding with opportunities for coverage, relaying, and information dissemination.
Problem
Systematic UAV-ground channel measurements and modeling remain ongoing, while finding optimal UAV flight paths is challenging for high-capacity performance.
Method
The article provides an overview of UAV-aided wireless communications through networking architecture, channel characteristics, design considerations, and three use cases.
Results
The survey highlights UAV-controlled mobility as a performance-enhancing technique for mobile relaying and D2D-enhanced UAV information dissemination.
Takeaways & Limitations
UAV-aided wireless communications offer research opportunities in ubiquitous coverage, relaying, and information dissemination, alongside energy management and replenishment needs.
Abstract
from arXiv · showhide
Wireless communication systems that include unmanned aerial vehicles (UAVs) promise to provide cost-effective wireless connectivity for devices without infrastructure coverage. Compared to terrestrial communications or those based on high-altitude platforms (HAPs), on-demand wireless systems with low-altitude UAVs are in general faster to deploy, more flexibly re-configured, and are likely to have better communication channels due to the presence of short-range line-of-sight (LoS) links. However, the utilization of highly mobile and energy-constrained UAVs for wireless communications also introduces many new challenges. In this article, we provide an overview of UAV-aided wireless communications, by introducing the basic networking architecture and main channel characteristics, highlighting the key design considerations as well as the new opportunities to be exploited.
I. INTRODUCTION
UAV-aided wireless communications can provide flexible connectivity where infrastructure coverage is unavailable, while exploiting mobility and short-range LoS links. Their deployment nevertheless requires specialized solutions for safety-critical control, dynamic connectivity, energy constraints, and interference management.
- Motivation: UAV-aided wireless communication provides connectivity for devices without infrastructure coverage caused by severe terrain shadowing or natural-disaster damage.The article presents this approach as a promising component of future wireless systems.
- Motivation: Low-altitude UAV systems are cost-effective, rapidly deployed, maneuverable, and can establish short-range LoS links that potentially improve communication performance.UAV state and mobility can be jointly adjusted with adaptive communications; for example, slowing down when channels are good sustains connectivity.
- Use Cases: Three typical use cases are ubiquitous coverage, relaying between distant users, and information dissemination or data collection for distributed devices.Examples include service recovery after infrastructure damage, emergency-response relaying, and precision-agriculture sensing.
- Challenges: UAV communications require stringent-latency and secure CNPC links, coordination for sparse intermittent topologies, energy-aware operation under SWAP constraints, and specialized interference management.These challenges affect safety-critical functions, communication and computation capabilities, endurance, connectivity, and neighboring aerial cells.
- Article Scope: The article overviews UAV networking architecture, channel characteristics, design considerations, and mobility-exploiting techniques for enhancing performance.It frames these topics as the article’s objective and scope.
II. BASIC NETWORKING ARCHITECTURE
The generic networking architecture for wireless communications with UAVs comprises two basic types of communication links: the CNPC link and the data link.
- Networking architecture: The generic UAV wireless-communications networking architecture is shown in Fig. 2.The architecture is presented as a generic framework for wireless communications with UAVs.
- Communication links: The architecture consists of two basic types of communication links.These links form the two fundamental categories in the generic networking architecture.
- Communication links: The two link types are the CNPC link and the data link.CNPC and data links are the named communication-link categories.
A. Control and Non-Payload Communications Link
CNPC links support safe UAV operation by carrying reliable, low-latency, secure two-way safety communications. They convey commands, status, and collision-avoidance information, while requiring protected spectrum, robust connectivity, and strong authentication.
- A. Control and Non-Payload Communications Link: CNPC links are essential for safe UAV operation and must provide highly reliable, low-latency, secure two-way communications, typically with low data-rate requirements.They exchange safety-critical information among UAVs and between UAVs and ground control stations.
- A. Control and Non-Payload Communications Link: CNPC information flow comprises command and control from ground stations, aircraft status reports to ground, and sense-and-avoid information among UAVs.CNPC links also remain necessary for emergency human intervention in autonomous UAVs.
- A. Control and Non-Payload Communications Link: Direct ground-station-to-UAV CNPC links are preferred for delay, while satellite-based secondary links can provide backup reliability and robustness.ATC links are additionally necessary when UAVs operate within controlled airspace, such as near an airport.
- A. Control and Non-Payload Communications Link: CNPC security must prevent ghost control by unauthorized agents using spoofed control or navigation signals, requiring powerful authentication and possibly physical-layer security.Ghost control is potentially catastrophic because it can place UAVs under unauthorized control.
B. Data Link · III. CHANNEL CHARACTERISTICS · A. UAV-Ground Channel
UAV-aided communications use data links for mission-related connectivity across direct access and wireless backhaul modes, while UAV-ground channels remain difficult to model because complex environments can disrupt expected LoS propagation. These channels also exhibit airframe shadowing, multipath effects, and environment- and frequency-dependent fading characteristics.
- B. Data Link: Data links support mission-related communications with ground terminals including terrestrial BSs, mobile terminals, gateway nodes, and wireless sensors.They enable direct mobile-UAV communication as well as UAV-BS, UAV-gateway, and UAV-UAV wireless backhaul.
- B. Data Link: Data-link capacity requirements range from several kbps for UAV-sensor links to dozens of Gbps for UAV-gateway wireless backhaul.Compared with CNPC links, data links generally tolerate greater latency and lower security requirements.
- B. Data Link: UAV data links can reuse application-specific spectrum such as LTE or use dedicated spectrum, including mmWave bands for enhanced high-capacity performance.The mmWave example applies to high-capacity UAV-UAV wireless backhaul.
- III. CHANNEL CHARACTERISTICS: Both CNPC and data links comprise UAV-ground and UAV-UAV channels with characteristics distinct from extensively studied terrestrial communication channels.The channel distinction motivates separate consideration of UAV-ground and UAV-UAV propagation.
- A. UAV-Ground Channel: Systematic measurement and modeling of UAV-ground channels remain ongoing because UAS operating environments are more complex than those of piloted aircraft systems.Piloted-aircraft ground sites are usually open areas with tall antenna towers, unlike many UAS settings.
- A. UAV-Ground Channel: Although LoS links are expected in most UAV-ground scenarios, terrain, buildings, and the airframe can occasionally block them.Recent measurements report severe airframe shadowing during aircraft maneuvering, requiring consideration in mission-critical operations.
- A. UAV-Ground Channel: Low-altitude UAV-ground channels can contain multipath components from reflection, scattering, and diffraction, with two-ray and stochastic Rician fading models commonly used.The two-ray model is mainly used over desert or sea, while the Rician model combines deterministic LoS and random scattered components.
- A. UAV-Ground Channel: Typical Rician factors are around 15 dB for L-band and 28 dB for C-band in hilly terrain.The Rician factor is the power ratio between LoS and scattered components and varies with the surrounding environment and frequency.
B. UAV-UAV Channel · IV. MAIN DESIGN CONSIDERATIONS
UAV-UAV channels are primarily line-of-sight dominated, with limited ground-reflection multipath but potentially higher Doppler frequencies caused by large relative UAV velocities. These characteristics motivate careful technology and spectrum choices, alongside design considerations covering path planning, energy-aware deployment and operation, and MIMO communications.
- B. UAV-UAV Channel: UAV-UAV channels are mainly dominated by the LoS component.
- B. UAV-UAV Channel: Limited multipath fading from ground reflections has minimal impact compared with UAV-ground or ground-ground channels.
- B. UAV-UAV Channel: Higher Doppler frequencies may arise from potentially large relative velocities between UAVs, directly affecting spectrum allocation for UAV-UAV links.
- B. UAV-UAV Channel: LoS dominance suggests mmWave communications could provide high-capacity UAV-UAV wireless backhaul.
- B. UAV-UAV Channel: Large relative velocity combined with mmWave frequencies could cause excessive Doppler shift.
- B. UAV-UAV Channel: More in-depth studies are needed to identify suitable technology for UAV-UAV links given their unique channel characteristics.
- IV. MAIN DESIGN CONSIDERATIONS: The main design considerations for wireless communications with UAVs include UAV path planning, energy-aware deployment and operation, and MIMO communications in UASs.
A. UAV Deployment and Path Planning · B. Energy-Aware Deployment and Operation
UAV deployment requires application-dependent path planning that balances communication performance against continuous trajectories and practical constraints. Because limited onboard energy restricts endurance, UAV systems also need coordinated replenishment and energy-efficient mobility and communication strategies.
- A. UAV Deployment and Path Planning: Path planning is crucial for high-capacity UAV communications because appropriate trajectories can significantly shorten communication distance.Finding the optimal flight path is challenging in general.
- A. UAV Deployment and Path Planning: Continuous UAV trajectories create infinitely many variables, while connectivity, fuel, collision, terrain, and time-varying constraints complicate optimization.A discrete-time 3D state-space approximation can represent position, velocity, and finite mobility transitions, often yielding MILP problems.
- A. UAV Deployment and Path Planning: Deployment depends on the application: multiple UAVs can cooperatively provide real-time cellular coverage, whereas one UAV can sequentially serve delay-tolerant ground nodes.For coverage, rotary-wing UAVs may hover as static aerial base stations, shifting design toward optimal separation and altitude.
- A. UAV Deployment and Path Planning: Urban coverage generally has an optimal UAV altitude because higher altitude increases free-space path loss but also improves the likelihood of LoS links.This tradeoff has been characterized to obtain the optimal altitude.
- B. Energy-Aware Deployment and Operation: Limited onboard energy fundamentally constrains UAS performance and operational duration, so deployment must replenish energy without noticeable service interruption.Energy-efficient operation must accomplish missions with minimum energy consumption.
- B. Energy-Aware Deployment and Operation: Inter-UAV cooperation enables sequential replenishment: one UAV leaves for energy replenishment while neighboring UAVs temporarily fill its service gap by adjusting positions or transmission power.Scheduling can follow dynamic load patterns, such as replenishing during low nighttime traffic for cellular coverage.
- B. Energy-Aware Deployment and Operation: Energy-efficient mobility controls maneuvers using consumption models based on speed, acceleration, and altitude, while avoiding unnecessary maneuvering or ascent.UAV energy use primarily supports propulsion and wireless communications.
- B. Energy-Aware Deployment and Operation: Energy-efficient communication minimizes communication-related expenditure while satisfying requirements, commonly by maximizing energy efficiency in bits/Joule; systematic UAV investigation remains under-developed.Energy efficiency is the number of successfully communicated data bits per unit energy consumption.
C. MIMO for UAV-Aided Communications
MIMO in UAV systems is constrained by poor scattering, SWAP-related costs, and difficult CSI acquisition, which limit practical gains. Nevertheless, carefully designed LoS arrays, multi-user MIMO, and mmWave operation offer ways to exploit MIMO, subject to deployment and alignment challenges.
- Challenges: Poor scattering in UAS environments limits MIMO spatial multiplexing, usually yielding only marginal rate improvement over single-antenna systems.This environmental limitation directly reduces the multiplexing benefit that motivates MIMO deployment.
- Challenges: Multiple antennas incur high signal-processing complexity, hardware and power consumption, while SWAP limitations make UAV deployment costly.MIMO performance also depends on accurate CSI, which is difficult to obtain in highly dynamic UAV environments.
- Opportunities: High spatial multiplexing gain remains attainable in LoS channels by designing antenna separation relative to carrier wavelength and link distance.This approach generally requires large antenna separation, high carrier frequency, and short communication range.
- Opportunities: Multi-user MIMO can restore spatial multiplexing in poor scattering by simultaneously serving sufficiently separated terminals with resolvable angular separations.The UAV array distinguishes terminals whose angular separations exceed its angular resolution.
- Opportunities: mmWave MIMO emphasizes array gain because of abundant bandwidth and high attenuation, but UAV mobility complicates directional beam alignment.Beam alignment must be addressed before mmWave MIMO can be practically employed in UAV systems.
V. COMMUNICATIONS WITH UAV CONTROLLED MOBILITY
UAV high mobility offers opportunities to improve wireless communication performance. The section focuses on UAV-enabled mobile relaying and D2D-enhanced UAV information dissemination.
- UAV high mobility offers unique opportunities for wireless communication performance improvement.
- The section discusses UAV-enabled mobile relaying as a key controlled-mobility technique.
- It also discusses D2D-enhanced UAV information dissemination.
A. UAV-Enabled Mobile Relaying
UAV-enabled mobile relaying exploits controlled UAV mobility to shorten source–UAV and UAV–destination links during both reception and relaying, particularly benefiting delay-tolerant applications. Compared with static relaying, it can improve path loss and throughput, although buffer size and communication-time trade-offs remain.
- A. UAV-Enabled Mobile Relaying: Mobile relaying continuously moves the UAV between source and destination to reduce link distances during both information reception and relaying phases.In half-duplex decode-and-forward relaying, each phase lasts δ seconds, determined by the maximum tolerable delay.
- A. UAV-Enabled Mobile Relaying: Compared with static relaying at the same initial position, mobile relaying always achieves shorter link distances, or better average channels, in both phases.The UAV flies toward the source or destination and may hover at the nearest location when time permits before returning to its initial position.
- A. UAV-Enabled Mobile Relaying: More than twice the throughput of static relaying is achieved at sufficiently high delay tolerance δ, and higher UAV velocity gives higher throughput for fixed δ.This result uses adaptive rate transmission and compares end-to-end spectrum efficiency in bps/Hz against maximum tolerable delay.
- A. UAV-Enabled Mobile Relaying: Data ferrying is expected to achieve smaller throughput because it provides less communication time, especially at low UAV speed or stringent delay requirements.Mobile relaying also involves a trade-off between on-board buffer size and achievable throughput.
B. D2D-Enhanced UAV Information Dissemination
D2D-enhanced UAV information dissemination combines UAV mobility with direct ground-node communication to efficiently distribute information to many nodes. Its two-phase protocol reduces UAV retransmissions and flying time, saving energy for small UAVs with limited onboard energy.
- Motivation: D2D communication can save UAV energy and reduce wireless-backhaul capacity requirements in UAV-aided communication systems.Existing terrestrial D2D techniques, including interference mitigation and spectrum sharing, can also apply to UAV-aided communications.
- Proposed Technique: D2D-enhanced UAV information dissemination targets efficient distribution to many ground nodes by exploiting both D2D communication and UAV mobility.The scheme considers one UAV distributing a common file while flying over an area containing many ground nodes.
- Baseline Limitation: Repeated UAV transmission requires substantial retransmissions and is limited by ground terminals experiencing the weakest UAV channels.Under this approach, the UAV repeatedly transmits the same file as it flies over different ground nodes until all successfully receive it.
- Two-Phase Protocol: The two-phase protocol first broadcasts a coded file, then has ground nodes exchange received data via D2D until all can decode it.Each node may receive only a fraction of the file, with different nodes receiving different portions.
- Benefits and Future Work: The scheme significantly reduces UAV retransmissions and total flying time, saving energy and benefiting small UAVs with limited onboard energy.For widely distributed nodes, clustering can improve short-range D2D file sharing; jointly optimizing path planning, coding, clustering, and sharing remains future work.
VI. CONCLUSIONS
The article overviews UAV-aided wireless communications through three use cases, networking architecture, channel characteristics, and design considerations. It highlights UAV-controlled mobility techniques and frames the identified challenges and opportunities as guidance for future system design.
- Conclusions: The overview covers UAV-aided ubiquitous coverage, relaying, and information dissemination.These three use cases structure the article’s treatment of UAV-aided wireless communications.
- Conclusions: The article introduces the basic networking architecture and main channel characteristics for UAV-aided wireless communications.It also discusses key design considerations for UAV communications.
- Conclusions: Two performance-enhancing techniques exploit UAV-controlled mobility: UAV-enabled mobile relaying and D2D-enhanced UAV information dissemination.These techniques are highlighted as ways to enhance performance through controlled UAV mobility.
- Conclusions: The described challenges and opportunities are intended to help researchers design and build UAV-enhanced wireless communications systems in the future.The article presents these challenges and opportunities as a path toward future research and system development.