UAV Relay Systems

Updated 9 March 2026

UAV relay systems are flexible aerial platforms that offer superior line-of-sight connectivity and rapid deployment to overcome ground-based obstacles.
They employ methods such as amplify-and-forward, decode-and-forward, and reconfigurable intelligent surfaces to optimize throughput and energy efficiency.
Real-world applications span military, IoT disaster recovery, maritime, and next-generation SAGIN networks, supported by advanced resource allocation and interference management strategies.

Unmanned Aerial Vehicles (UAVs) function as agile, high-altitude relay platforms in wireless communications, providing superior line-of-sight (LoS) conditions and rapid deployment capabilities compared to traditional terrestrial relays. By exploiting three-dimensional (3D) mobility and elevation, UAV relays overcome limitations imposed by ground-based obstacles, multipath, and coverage holes. They are now integral to military, emergency, IoT, cellular, maritime, and space–air–ground integrated networks (SAGIN), supporting both legacy and advanced communications protocols with configurations ranging from single UAVs to coordinated swarms.

1. Principles and Typology of UAV-Based Relay Systems

UAV relay systems are typically modeled as multi-node, two-hop or multi-hop wireless links: a source transmits to a UAV (or swarm) which, after possibly applying signal processing operations, forwards the message to one or more destinations. Key architectural classes include:

Active Aerial Relays (AAR): Hardware-based relays equipped with full RF transceivers, performing amplify-and-forward (AF) or decode-and-forward (DF) operations, often supporting MIMO and beamforming (Al-Kamali et al., 27 Jan 2026).
Aerial Reconfigurable Intelligent Surface (ARIS) Relays: UAV-carried passive meta-material arrays that shape the wireless channel through programmable reflection and phase shifts, enabling low-power, quasi-real-time reconfiguration (Al-Kamali et al., 27 Jan 2026).
Multi-hop and Swarm Relays: Distributed UAV networks forming connected relay chains, with topology and traffic engineered for dynamic or coverage-constrained environments (Gholami et al., 2020).

UAV relays are fundamentally distinguished from terrestrial relays (TR) by their 3D placement flexibility, the ability to rapidly circumvent or cover ground obstructions, and their fast deployment in denied, hazardous, or infrastructure-poor regions (Al-Kamali et al., 27 Jan 2026).

2. Channel and Propagation Characteristics

UAV relays leverage LoS-dominated air-to-ground (A2G) and air-to-air (A2A) channels, typically modeled by free-space path-loss (FSPL) and log-distance path-loss exponents. Empirical measurement confirms that for VHF bands, placing a UAV relay at 500 m AGL achieves path-loss exponents of approximately η ≈ 2.6, a substantial improvement over ground-to-ground NLoS links (η ≈ 3.3) (Galkin et al., 2023). Communication ranges exceeding 50 km have been documented using portable 5 W radios and low-gain whip antennas. However, multipath, Fresnel-zone obstructions, and partial LoS losses remain significant, especially at lower altitudes or in urban, wooded, or cluttered environments (Galkin et al., 2023).

In realistic deployments, relay link performance is jointly determined by altitude, antenna configuration, local terrain, atmospheric conditions, and the electromagnetic propagation environment. Strategic altitude selection (e.g., 1–3 km AGL for VHF) can reduce path-loss exponents to near the free-space ideal (η → 2) (Galkin et al., 2023).

3. Relay Protocols, Strategies, and Resource Optimization

UAV relays employ a variety of protocol and optimization strategies, including:

AF and DF Relaying: AF relays amplify received analog signals (subject to noise enhancement), whereas DF relays decode, optionally error-correct, and re-encode, improving resilience at the expense of delay (Al-Kamali et al., 27 Jan 2026).
Store-then-Forward (SAF): Mobile UAV relays store received data and forward it when the relay trajectory brings the UAV close to the destination, maximizing throughput under time-varying channel conditions (Lin et al., 2020).
Energy-Efficient Positioning: Relay movement and placement optimization jointly minimize propulsion energy and maximize communications quality. Algorithms such as Energy-aware RElay Positioning (EREP) plan power-optimal cruise trajectories under throughput and delay constraints (Rodrigues et al., 2020).
LP/MILP Formulations: Joint UAV deployment and routing are formulated as mixed-integer programs; real-time-tractable LP-relaxation and rounding heuristics achieve near-optimal deployments in mobile, clustered, or capacity-limited ground networks (Gholami et al., 2020).
Resource Allocation: In OFDMA and multi-band networks, joint optimization of subchannel assignment, relay trajectory, and power allocation ensures proportional fairness and maximizes sum-throughput (Zeng et al., 2021).

Coverage planning tools routinely account for path-loss exponents (η ≈ 2.5–2.7 at 500 m AGL), receiver sensitivity (e.g., P_rx,min ≈ –100 dBm), and multihop or relay chains as needed to achieve corridor, areal, or mesh connectivity (Galkin et al., 2023).

4. Interference Management, Security, and Covert Relaying

UAV relays are increasingly leveraged for interference avoidance, network resilience under intentional jamming, and secure/covert communications:

Interference-Aware Placement: Optimal relay positioning in the presence of major or stochastic interferers is handled via closed-form geometric solutions and distributed algorithms, with dual-hop and multi-hop designs ensuring minimal relay count for a specified SIR target (Hosseinalipour et al., 2019, Hosseinalipour et al., 2019).
Collaborative Beamforming in Swarms: UAV swarms can form distributed antenna arrays (UVAAs) to conduct secure relaying via spatial nulling and collaborative beam steering, maximizing legitimate throughput while minimizing eavesdropper rates and propulsion costs. Multi-objective metaheuristics (e.g., improved multi-objective grasshopper optimization) solve the high-dimensional placement, beamforming, and scheduling problem optimally (Zhang et al., 2023).
Covert and Secure Relaying: UAV relays combine DF operations with friendly jamming to simultaneously maximize throughput to legitimate users while robustly enforcing covertness constraints against ground-based detection and eavesdropping. The optimization frameworks employ fractional programming, Pinsker’s inequality, and alternating convex algorithms to jointly design relay trajectory, power profiles, and time-switching factors (Jiang et al., 2024).

Such frameworks support progressive and adaptive trade-offs between covertness, energy efficiency, and secrecy rates under real-world detection uncertainty.

5. Applications and Experimentally Validated Deployments

UAV relay technology is validated across a wide diversity of domains:

Public Safety and Military: Integration with existing VHF/UHF equipment provides rapid, wide-area digital voice coverage for emergency personnel, military convoys, and disaster response up to 10×–12× ground-only baseline ranges (Galkin et al., 2023, Firouzjaei et al., 10 Feb 2025).
IoT and Disaster Networks: UAV relays in simultaneous wireless information and power transmission (SWIPT) architectures enable energy harvesting from ground user transmissions, extending mission time and user capacity in energy-constrained, post-disaster networks (Firouzjaei et al., 10 Feb 2025, Yin et al., 2017).
Maritime Links: In port and harbor environments, UAV-mounted DF relays—especially via landing-spot assisted perch-and-fly regimes—significantly mitigate shadowing from large vessels, achieving up to 90% energy savings at <2% data-rate loss relative to energy-intensive hovering (Çağan et al., 2023).
SAGIN and Semantic Communications: In next-generation 6G architectures, UAVs bridge satellite downlinks (often using semantic communication on the first hop) with heterogeneous ground clusters, leveraging intelligent resource allocation and dual-mode relay strategies to maximize rate and coverage (Yin et al., 23 Nov 2025).

Additionally, UAV swarms operating as AF-MIMO relays in cellular networks demonstrate near-linear capacity gains with the number of relay antennas, provided inter-UAV spacing is optimized to meet LoS-MIMO orthogonality, and hybrid power-antenna scaling is judiciously managed (Hanna et al., 2019, Hu et al., 2018).

6. Design Guidelines, Trade-offs, and Algorithmic Insights

The utility of UAV relays is critically shaped by joint consideration of:

Altitude, Antenna, and Propagation: Higher altitudes and appropriately selected wideband antennas increase LoS probability and reduce multipath impacts; empirical exponents η ≤ 2.6 can be reached at 0.5–1 km AGL. Match vertical polarization and minimize UAV/antenna pattern distortion (Galkin et al., 2023).
Energy and Endurance: Propulsion dominates energy consumption; continuous cruise at optimal speed v* (not hovering) maximizes endurance (Rodrigues et al., 2020).
Multihop and Mobility-Awareness: Periodic re-planning of relay positions and routes in mobile, multi-hop backbones recovers significant throughput otherwise lost to static deployments (up to 40%) (Gholami et al., 2020). Energy-aware, centralized, and distributed algorithms exist for relay selection, placement, and link scheduling.
Resource-Aware Relaying: Subchannel, power, and trajectory co-optimization is essential for combined throughput, fairness, and UAV longevity, especially in OFDMA and clustered ground scenarios (Zeng et al., 2021, Chen et al., 2018).
Security, Covertness, and EW Resilience: Beamforming, null-steering, friendly jamming, and adaptive resource allocation form the core of robust relay design in contested and denial-prone operations (Zhang et al., 2023, Jiang et al., 2024).

Future directions identified include low-weight energy-harvesting UAV airframes, resilient A2G channel modeling, integrated spectrum sharing, stealth techniques, secure swarm control, and the use of AI/digital twins for autonomous multi-UAV relay management (Al-Kamali et al., 27 Jan 2026).

7. Performance Benchmarks and Mission-Critical Trade-offs

Quantitative metrics for UAV relays include attainable range, supported throughput, energy efficiency, coverage area, SIR/SINR under interference, and mission-time to service completion. Explicit decision-theoretic frameworks, such as the Mission-Critical Relay Effectiveness Score (MCRES), aggregate relay capabilities (mobility, jamming resilience, deployment speed, stealth, coverage, autonomy) under mission-specific weightings to select between aerial, terrestrial, and hybrid relays (Al-Kamali et al., 27 Jan 2026).

Degree of performance improvements validated in operational campaigns are summarized as follows:

Scenario	Range/Coverage Gain	Throughput/Rate	Energy Efficiency	Security/Covert Gain
VHF Tactical Relay	10–12× baseline	Digital voice at >50 km (Galkin et al., 2023)	n/a	n/a
Maritime Perch-and-Fly	~3× over non-relay	<2% loss over hover	90% lower than hover	n/a
SWIPT Relaying in IoT	+30% serviced users	+20% sum-rate	–25% mission time	n/a
Secure Swarm Beamforming	Not applicable	10× eavesdropper rate reduction	5–10× less than multi-hop	Yes (active nulling)
Covert/Secrecy Relay	Not applicable	Maintained at constraint	10–20% > static relay	Robust under location uncertainty

All entries are derived from cited field experiments and simulation studies (Galkin et al., 2023, Çağan et al., 2023, Firouzjaei et al., 10 Feb 2025, Zhang et al., 2023, Jiang et al., 2024).

Rigorous design, placement, and protocol choices allow UAV relays to operate as energy-efficient, dynamic, secure, and coverage-extending links across a spectrum of hostile, denied, and infrastructure-degraded environments.

Key References:

Experimental evaluation of UAV VHF relaying (Galkin et al., 2023)
Military relay survey and MCRES framework (Al-Kamali et al., 27 Jan 2026)
Mobility-aware multi-hop UAV backbones (Gholami et al., 2020)
SWIPT disaster IoT UAV relay (Firouzjaei et al., 10 Feb 2025)
Maritime deployment strategies (Çağan et al., 2023)
Propulsion-aware relay planning (Rodrigues et al., 2020)
Security/beamforming in UAV swarms (Zhang et al., 2023)
Semantic relaying in 6G SAGIN (Yin et al., 23 Nov 2025)
Store-then-forward/mobility relay protocols (Lin et al., 2020)
Interference-aware relay optimization (Hosseinalipour et al., 2019, Hosseinalipour et al., 2019)
Topology/terrain-aware local placement (Chen et al., 2018)
Outage, power allocation, capacity benchmarks (Tu et al., 2019, Hu et al., 2018, Hanna et al., 2019)