In this contribution, a high-resolution parameter estimation algorithm is derived based on the Space-Alternating Generalized Expectation-maximization (SAGE) principle for extracting multipath parameters from the output of sliding correlator (SC). The SC allows calculating channel impulse responses with a sampling rate less than that required by Nyquist criterion, and hence is widely used in real-time wideband (e.g., >500 MHz) channel sounding for the fifth generation wireless communication scenarios. However, since the sounding signal needs to be sent repetitively, the SC-based solution is unacceptable for time-variant channel measurements. The algorithm proposed here estimates multipath parameters by using a parametric model of both low- and high-frequency components of the SC's output. The latter was considered as distortions and discarded in the conventional SC-based channel sounding. The new algorithm allows estimating path parameters with less repetitions of transmitting the sounding signal and still exhibits higher estimation accuracy than the conventional method. Simulations are conducted and illustrate the root mean square estimation errors and the resolution capability of the proposed algorithm with respect to the bandwidth and the length of the SC's output. These studies pave the way for measuring time-variant wideband propagation channels using SC-based solutions.
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