Death/Birth and SNR Detection for Vehicular Kalman Channel Trackers

Wireless communication demand is increasing requirements due to expected smart mobility as well as modern vehicular technologies, such as Unmanned Air Vehicles (UAVs) or High-Speed Rail (HSR). In the latter scenario, high mobility through different physical environments, such as from viaducts to cuttings or tunnels, results in a fast variation of the multipath structure, giving rise to the phenomenon of birth-death of taps. To exploit the temporal correlation of each tap, however, a Kalman filter (KF) could be used; but KF's performance degrades catastrophically unless tap birth/death can be synchronically detected. To address this issue, several solutions based on particle filtering have been proposed, albeit with a prohibitive complexity. More recently, a Simplified Maximum A Posteriori (SMAP) algorithm for tap birth/death detection has been developed for the case where there is no signal-to-noise ratio (SNR) variation. With a similar purpose in mind, this paper develops a theoretical framework to understand death/birth detection when SNR is dynamical and may drift. This paper also analyzes how different quasi-ideal SNR detectors affect the SMAP algorithm's performance.