arXiv:2602.170193 PaperLens breakdowns

Beyond Average-Channel-Based Rate Approximations: UAV Trajectory and Scheduling Optimization With Expected Rate Consideration

This paper tackles the challenge of optimizing UAV trajectories, user scheduling, and time-slot durations in wireless communication systems to minimize mission completion time, while strictly adhering to minimum expected spectral efficiency (SE) constraints. Unlike previous methods that overestimate SE by using average channel gains, the authors propose a novel quadrature-based approximation that numerically integrates SE over channel distributions, providing a conservative yet tractable lower bound for reliable optimization.

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Key Takeaways

Conventional average-channel-based SE approximations systematically overestimate true expected SE due to Jensen's inequality, leading to unreliable UAV communication designs.

A novel quadrature-based approximation, using CDF-domain discretization, provides a conservative and tractable lower bound for expected SE, explicitly accounting for probabilistic LoS and fading effects.

The problem is formulated as a mixed-integer nonconvex optimization to minimize mission completion time under expected-SE constraints.

A penalty-based block coordinate descent (BCD) framework is developed, alternately optimizing scheduling, trajectory, and time-slot durations.

Successive convex approximation (SCA) and quadratic transform techniques are employed to handle the problem's nonconvexities.

The proposed method strictly satisfies minimum expected-SE constraints and achieves significantly shorter mission completion times compared to conventional approaches.

Core Concepts

Expected Spectral Efficiency (SE)

Expected SE is the true measure of average data rate reliability, and its accurate estimation is paramount for robust system design.

Average-Channel-Based SE Approximation

This common approximation is computationally convenient but yields an upper bound on the true expected SE, making it unreliable for designs requiring strict performance guarantees.

Jensen's Inequality

Jensen's inequality is a fundamental tool for understanding the relationship between the expectation of a function and the function of an expectation, particularly crucial for nonlinear system analysis.

Probabilistic LoS Channel Model

The probabilistic LoS model captures the dynamic nature of air-to-ground channels, making UAV trajectory optimization more effective by allowing the UAV to influence its link quality.

Why It Matters

This research fundamentally changes how we design and operate UAV-assisted wireless communication systems. By ensuring that minimum data rate requirements are *actually* met in stochastic environments, it prevents costly mission failures, improves service reliability for critical applications (like emergency response or remote sensing), and allows for more efficient use of UAV resources. It moves UAV communication from 'hope for the best' to 'guarantee the performance'.

**Disaster Relief & Emergency Communications**: UAVs providing temporary network coverage in areas with damaged infrastructure, ensuring critical data transfer (e.g., sensor data, video feeds) meets minimum reliability thresholds.**Precision Agriculture**: Drones collecting high-resolution sensor data from large farms, guaranteeing sufficient data throughput for real-time analysis and decision-making.**Remote Industrial Monitoring**: UAVs inspecting pipelines, power lines, or remote facilities, reliably transmitting inspection data (e.g., thermal imagery, structural integrity scans) back to a central hub.**Package Delivery & Logistics**: Drones communicating with ground stations or other drones for coordination and status updates, ensuring reliable data exchange for safe and efficient operations.**Search and Rescue Operations**: UAVs relaying critical information (e.g., location data, vital signs) from isolated individuals to rescue teams, where data reliability is paramount.