# Communication Infrastructure Design for Reliable UAV Operations in Air Mobility Corridors
## 2 Materials and Methods
### Adapting Air Mobility Communication Design in Broken-Line UAV Corridor Topologies
The deployed radio stations serve not only for communication but also as navigation aids, like traditional aviation very high-frequency omnidirectional range (VOR) stations. This dual-purpose functionality enables UAVs to navigate by homing toward the signal from the next node station, determine their precise position through signal strength triangulation from multiple stations, and maintain position within corridor boundaries through signal strength thresholds. This radio-based navigation approach is particularly valuable in urban canyons where GPS signals may be unreliable due to multipath effects or signal blockage by buildings. It is important to emphasize that the failure probabilities applied in the Markov chain analysis are configurable parameters introduced for the purpose of sensitivity evaluation and comparative robustness analysis. The model is not intended to reflect exact empirical failure rates, which may indeed be near zero in stable ground-based communication infrastructures. Instead, the objective is to examine the behavior of different repeater deployment strategies under rare but safety-critical degradation scenarios, including power outages, signal interference, cyber-physical disruptions, or long-term hardware aging. This approach is particularly relevant to the requirements of UAM and last-mile delivery UAV applications, where the maximum tolerable probability of catastrophic subsystem failure is often constrained to \(10^{-9}\) per flight hour. By allowing the failure rate parameters to be adjusted, the proposed model remains applicable across a range of system reliability targets and regulatory compliance levels. By extending the deployment strategies and reliability analysis to non-linear corridors, this approach provides a comprehensive framework for designing robust communication infrastructure that supports safe UAV operations in complex urban environments while maintaining optimal resource utilization. Parameter Estimation Methods for Markov Model State-Transition Probabilities  
The accuracy of the proposed Markov reliability models depends critically on the proper estimation of state-transition probability parameters. For existing communication infrastructure, failure rates \(\lambda\) can be estimated from historical maintenance records. For new deployments, system-level failure rates can be derived from telecommunications industry standards. For outdoor radio equipment, typical \(\lambda\) values range from \(1\times 10^{-6}\) to \(1\times 10^{-4}\) failures/hour, corresponding to a mean time to failure (MTTF) of 10,000 to 1,000,000 h.  
The repair rate \(\mu\) can be estimated from service-level agreements and historical repair data, accounting for detection time (automated monitoring vs. manual discovery), response time (technician dispatch and travel), diagnosis and repair time, and testing and restoration time. Urban deployments typically achieve the mean time to repair (MTTR) of 2-24 h (\(\mu=0.04-0.5\) repairs/hour), while remote locations may require 24-72 h (\(\mu=0.014-0.04\) repairs/hour). UAV communication request arrival rates, \(\varphi\), depend on corridor utilization patterns. It can be estimated through traffic simulation models based on projected UAV operations, pilot deployment data from test corridors, or analogous systems such as cellular handoff rates in transportation corridors. The service rate, \(\psi\), represents the completion rate of UAV communication sessions. Typical UAV communication sessions for navigation and control range from 30 s to 5 min, yielding \(\psi\) values of 0.003-0.033 sessions/second. Estimated parameters should be validated using Kolmogorov-Smirnov tests for exponential distribution assumptions. For operational systems, parameters may vary over time due to equipment aging effects on failure rates, seasonal variations in repair times, and traffic pattern evolution. It is required periodical parameter updates.