Toward Smart City Skyways: 6G-Enabled Antenna Architectures and Adaptive Channel Modeling for Urban Low-Altitude UAV Network

Abstract

Low-altitude unmanned aerial vehicle (UAV) communication in cities is affected by frequent blockage, rapidly changing propagation paths, limited onboard power, and strict latency requirements. These conditions make it difficult to evaluate channel models, antenna designs, and communication algorithms in a single layer. This review discusses how sixth-generation research approaches the problem through urban channel characterization, reconfigurable intelligent surfaces, metamaterial antennas, and data-driven communication control. It covers material-dependent propagation, dynamic blockage, channel prediction, beam management, trajectory planning, resource allocation, federated learning, and integrated sensing and communication. The literature is compared by operating frequency, urban scenario, validation basis, and trade-offs among reliability, delay, energy consumption, and hardware complexity. Results reported for any one method remain conditional and do not show that an end-to end UAV link will operate reliably under representative urban conditions. Such performance also depends on representative channel measurements, update latency, hardware nonidealities, and the size, weight, power, and cost limits of the platform. The review identifies shared datasets, integrated field experiments, and reproducible benchmarks, including Digital Twin evaluations, as the next requirements for translating laboratory and simulation results into dependable, scalable Smart City Skyways.