# MPSi

MPSi replaces the data-dependent, variable-iteration nonlinear refinement of classical channel sounding with a small path-count network plus a fixed-depth unfolded Levenberg–Marquardt refiner, estimating each multipath component's complex gain, angle of arrival and delay from a single pilot observation. In two ray-traced scenarios, a small cell (Bahen) and a dense urban area (Dundas), its initial-access and full-channel-estimation performance is comparable to an enhanced RIMAX baseline while using a fixed and substantially smaller number of refinement iterations; the reconstructed channels give bit-error-rate performance close to the perfect-channel reference.

MPSi replaces the data-dependent, variable-iteration nonlinear refinement of classical channel sounding with a small path-count network plus a fixed-depth unfolded Levenberg–Marquardt refiner, estimating each multipath component's complex gain, angle of arrival and delay from a single pilot observation. In two ray-traced scenarios, a small cell (Bahen) and a dense urban area (Dundas), its initial-access and full-channel-estimation performance is comparable to an enhanced RIMAX baseline while using a fixed and substantially smaller number of refinement iterations; the reconstructed channels give bit-error-rate performance close to the perfect-channel reference.