Sequential MAP Parametric OFDM Channel Estimation for Joint Sensing and Communication

Uplink sensing is still a relatively unexplored scenario in integrated sensing and communication which can be used to improve positioning and sensing estimates. We introduce a pilot-based maximum likelihood, and a maximum a posteriori parametric channel estimation procedure using an orthogonal frequency division multiplexing (OFDM) waveform in uplink sensing. The algorithm is capable of estimating the multipath components of the channel, such as the angles of arrival, departure, path coefficient, and the delay and Doppler terms. As an advantage, when compared to other existing methods, the proposed procedure presents expressions for exact alternating coordinate updates, which can be further improved to achieve a competitive multipath channel estimation tool.

Doppler-Robust Maximum Likelihood Parametric Channel Estimation for Multiuser MIMO-OFDM

The high directionality and intense Doppler effects of millimeter wave (mmWave) and sub-terahertz (subTHz) channels demand accurate localization of the users and a new paradigm of channel estimation. For orthogonal frequency division multiplexing (OFDM) waveforms, estimating the geometric parameters of the radio channel can make these systems more Doppler-resistant and also enhance sensing and positioning performance. In this paper, we derive a multiuser, multiple-input multiple-output (MIMO), maximum likelihood, parametric channel estimation algorithm for uplink sensing, which is capable of accurately estimating the parameters of each multipath that composes each user's channel under severe Doppler shift conditions. The presented method is one of the only Doppler-robust currently available algorithms that does not rely on line search.