This letter proposes a low-complexity one-snapshot two-step signature estimation algorithm for a sparse multipath near-field spatial-wideband system. With upcoming sub-THz systems expected to have a large number of antennas, the transmitted wideband signal is not only sensitive to the physical propagation delay across the array aperture but the resulting wavefront is no longer locally planar. We use a combination of discrete Fourier and discrete linear chirp transform-based techniques to estimate the spatial wideband signature of such a system. Further, we propose an iterative neighbourhood search to acquire super-resolution estimates of the scatterer locations, delays and angle of arrival of the multipaths and show that they are asymptotically optimal approaching their respective Cramer- Rao bounds.Â

Next-generation communication systems operating in the mm-Wave and sub-THz bands face high path loss, which can be mitigated by ultra-massive antenna arrays. However, high-resolution quantization in these systems is often impractical, leading to a growing interest in low-resolution, particularly 1-bit ADCs. This letter addresses joint angle and range estimation using 1-bit massive uniform linear arrays (ULA) in wideband near-field systems. We propose a MUSIC-based 1-bit joint angle-range estimation algorithm (JARE-MUSIC) over a near-field tapped-delay line channel model, thus, demonstrating that existing MUSIC-based methods can be adapted for effective wideband near-field localization even under extreme quantization.

The design and development of sub-Terahertz (THz) communication systems entail the need for new channel models that can precisely predict channel characteristics at such frequencies (>100 GHz) in outdoor and dynamic environments. This work proposes a novel hybrid-stochastic ultra-wideband channel model for sub-THz bands, developed within the framework of a class of spatio-temporal stochastic processes called ambit-process. The proposed model is capable of supporting bandwidths of upto 10 GHz. The spatio-temporal evolution of the ambit framework allows for a reasonably accurate and tractable characterization of the fading statistics and multipath propagation of a cellular channel with good spatial consistency. We leverage a recently proposed low-complexity ambit-process based channel simulation algorithm with necessary modifications to study key features of the outdoor sub-THz channel like associated diffused scattering, molecular absorption, spatio-temporal correlations, and consistency between the time-evolving delay and Doppler of the multipaths. Simulation results on path loss, delay spread, and channel correlation indicate that the ambit model accurately captures the typicalities of an urban microcellular sub-THz channel and agrees well with the measurement results reported in the literature.

The design and development of sub-Terahertz (sub-THz) cellular systems entail the need for new channel models that can precisely predict channel characteristics beyond 100 GHz in outdoor and dynamic environments. This work proposes a novel multiple-input and multiple-output (MIMO) channel model for cellular communication, developed within the framework of a class of spatio temporal stochastic processes called ambit-process. The modeling methodology effectively captures the typicalities of sub-THz propagation like molecular absorption and scattering of the evolving multipaths while accounting for the propagation delay of electromagnetic waves across large array apertures deployed at the transmitter and the receiver. This allows for an accurate characterization of the spatial-wideband effect along with other relevant spatio-temporal attributes of the channel. Numerical simulations indicate a good level of agreement between the spectral efficiency and spatio-temporal correlation of the proposed model against a state-of-the-art stochastic Terahertz (THz) channel model and measurements reported in literature.