An Empirical Air-to-Ground Channel Model Based on Passive Measurements in LTE

In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle channels is introduced. The downlink signals of an in-service long-time-evolution network, which is deployed in a suburban scenario were acquired. Five horizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell-specific signals, and the underlying physical propagation mechanisms are interpreted by exploiting the propagation graph modeling approach. Based on the CIRs, the parameters of multipath components are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread, and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.